Disadvantages Of Arv Treatment Health And Social Care Essay

3602 words (14 pages) Essay

1st Jan 1970 Health And Social Care Reference this

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Herbs have been used extensively in hopes of improving immune response and reducing symptoms. No known herbal remedy has been shown to cure AIDS or even reduce chances of AIDS-related infections. Still, some herbs can be worth trying if used safely and in consultation with a qualified practitioner who not only understands herbs but also has experience treating AIDS and HIV infection.

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Immunity-boosting herbs (such as Astragalus, Echinacea, and Ginkgo) may help revive an ailing immune system, and certain herbs (such as Garlic) may help battle bacteria and viruses. Deglycyrrhizinated licorice can soothe the mouth and throat ulcers that often accompany full-blown AIDS.

Unfortunately, there is no known scientific explanation yet, for how herbs have these ‘powers’ in treating AIDS and the only information available about how useful herbal treatments and remedies can be, is based on the knowledge gained from people living with HIV/AIDS. This means that not all herbs and remedies have the same effect on all people.

Some communities have their own knowledge of health and nutrition, based on local traditions and culture. This may complicate the administration of herbal remedies from region to region, as the fundamental factor is now depending whether the patient is willing to cross cultures in order to obtain treatment.

In some extreme cases, any external medical recommendations that a patient may receive is compared with their cultural practices and the recommendations of their traditional healers. Patients will only take action if the recommendations they receive appear to make sense and provide some benefit.

Ironically, some traditional beliefs and food practices may not be useful at all, judging that a herb like Garlic root should work whether the patient is of Chinese or African descent. Patients with HIV/AIDS often become frustrated with management of the disease and are willing to try anything in the hope of staying healthy and living longer.

One of the greatest disadvantages is that HIV/AIDS is not a traditional illness and so far, there is no hard evidence to believe that traditional medicines or herbal remedies can treat HIV and cure AIDS. However, certain herbal medicines may help to treat many of the symptoms of opportunistic infections that are part of AIDS. While some of these medicines may be undoubtedly helpful, others may be dangerous as they may do more harm than good. This happens when the patient mixes pharmaceutical drugs and herbs resulting in contra-indications or when they take certain foods that should be otherwise avoided.

The notion that herbal medicines are natural and therefore safe is as widespread as it is misleading. Some of these remedies have been associated with severe adverse effects caused by the toxicity of the herbal ingredients. Others may cause problems because of contamination or adulteration [9].

Herbs and spices should be used in moderate amounts. Exceeding these amounts may cause problems and have a toxic effect; moreover, the function of the herbs and spices will not be increased. Herbs do not replace healthy eating and should not be used in place of a healthy and balanced diet but they do retain the body’s natural pH (alkaline) and this in turn, as discussed before, forces the microzymes to stop mutating into bacteria, viruses and funguses that cause opportunistic infections.

2.1.7 Advantages of Herbal Treatment:

On general note, Herbal therapies seek to boost patients’ immune systems, inhibit opportunistic infections, alleviate symptoms, and inhibit HIV itself.

Herbal medicines are very cheap in comparison to the conventional form of medication

Herbal medicine helps the body to maintain its natural pH, which is alkaline; this in turn starves and inhibits all adverse microzymes from growing or mutating.

Herbal medicines can be consumed without the aid of any kind of prescription, although a herbal or medical practitioner has to be consulted prior

Herbal medicines are known to be more productive in comparison to other forms of medication in curing certain conditions.

Herbal medicines offer long lasting benefits in terms of overall wellness.

In certain situations, Herbs are considered a possible means to minimize drug side effects.

Unlike with the convectional highly active antiretroviral therapy (HAART), herbs do not need to work in combination in order to get effective results

Herbs are readily available and once a patient knows which herb to use, he/she can grow their own.

2.1.8 Disadvantages of Herbal Treatment:

Curing period is usually longer in comparison to conventional medication

Drug-interactions can be hazardous to a patient ,if they decide to mix herbs and drugs

Herbal medicines are known to be ineffective against serious ailments

Herbal medicines are taken without prescription which means that in some cases, individual might be undergoing a trial and error process with their medication.

Herbal medicines can cause allergic reactions in some cases

Herbal medicines will not eliminate the HI virus out of the body

Most governments do not approve of any kind of herbal medication. It’s usually consumed upon the person’s own risk, and when it comes to branded herbal supplements one can’t expect any kind of quality assurance

2.2 Expert Systems and their use on the Internet

2.2.0 Expert systems

An expert system is a computer program that incorporates concepts derived from experts in a field, uses the available information, heuristics and inference to suggest solutions to problems in that particular discipline or give advice.

An expert system should have good decision making, this is strongly dependent on various capabilities that include the effective acquisition, storage, distribution and sophisticated use of the human experts in the field in question.

The most widely used way of representing domain knowledge in expert systems is as a set of production rules which is also how humans generally infer decisions. Expert systems were made to provide knowledge and advice to a larger number of users than one user. An Expert system can be viewed as a teaching tool because it is equipped with the unique features which allow the users to ask questions on how, why and what format, expert systems also allow automation of many tasks that could not be effectively handled by human experts.

In addition, an Expert system attempts to emulate how a human expert solves a problem, mostly by the manipulation of symbols instead of numbers. As a result because of the low cost per user and automation of numerous tasks ,expert system making has become very attractive and in the long run is much cheaper than getting human expert advice, its development is however relatively costly but its operation is easy and quite cheap.

Maintenance is easy as well because once an expert system is developed it is simple to add new information to the knowledge base and new rules can be developed.

2.2.1 Advantages of Expert systems

Availability: The expert system is always available 24 hours a day and will on no account tire

Can capture scarce expertise, collected from a number of experts and integrate their opinions.

Consistency: The computer does not make common futile human mistakes such as forgetting, getting drunk or strike when it is most needed.

Data can be kept up-to-date.

Efficiency: Expert systems have an increased output and productivity as well as decreased decision making time.

Flexibility: Expert systems can operate in hazardous environments. They can also work with incomplete or uncertain information.

Scalability: The system can be used at a distance over a network therefore can reach a large population.

The computer can store far more information than a human expert.

2.2.2 Disadvantages of Expert systems

Expertise can be hard to extract from humans

Expert system users have natural cognitive limits (therefore can not perform as perfectly as a human)

Experts’ vocabulary is often limited and highly technical

Expert systems may not be able to arrive at valid conclusions and sometimes produce incorrect recommendations

Knowledge is not always readily available

Lack of trust by end-users

Most experts have no independent means to validate their conclusions

2.3 Structure of Expert systems

A typical expert system consists of:

A knowledge base; this contains the specific domain knowledge that is used by an expert to derive conclusions from facts

The inference engine, which is responsible for using the rules and facts to derive conclusions whether it is through forward, backward chaining or a combination of both.

An explanation system, which provides information to the user about how the inference engine arrived at its conclusions

A fact database, which contains the case-specific data that are to be used in a particular case to derive a conclusion and

A User interface, which provides access to the inference engine, the explanation system, and the knowledge-base editor.

KnowledgeBase

Fact

Database

Expert System Shell

Inference

Engine

Knowledge

Base Editor

Explanation

System

User Interface

User

Figure2.1 A basic structure of an Expert System.

An Expert System can be rule-based, frame based or both. In a rule-based system, the knowledge base is a database of rules. Rule-based systems are computer systems that use rules to provide recommendations or diagnoses, or to determine a course of action in a particular situation or to solve a particular problem.

Its line of reasoning or the inference engine technique can be forward chaining, backward chaining, or a combination of both and the Rete algorithm.

2.4 Inference Engine

The knowledge in the knowledge base is used for reasoning and inferring conclusions. An inference rule is an abstract structure that contains a set of rules that mathematically delineates a (usually infinite) set of finite length strings over a (usually finite) alphabet. It is a two part structure using First Order Logic for knowledge representation.

If

<conditions>

then

<actions>

The brain of expert system is the inference engine which is generally a large number of rules and facts. The inference engine matches facts and data, which is in the fact database against the inference rules to infer conclusions which result in actions. The process of matching the new or existing facts against inference rules is called Pattern matching.

Pattern matching in the inference engine can use any of the following algorithms:

Linear

Rete

Treat

Leaps

Most of the rule engines under study implement and extend the Rete algorithm. Leaps is also used widely but is questionable due to poor maintenance. Rete based engines have proprietary enhancements to the Rete algorithm like RetePlus, Rete III and ReteOO.

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The Rete algorithm is responsible for ensuring that there is a clear distinction between rules and facts in the database. This algorithm takes the form of a network, with nodes and paths. Each path from the root node to a leaf in the tree represents the left-hand side of a rule. Each node stores details of which facts have been matched by the rules at that point in the path.

In situations where new data or facts are added, it means the Rete algorithm will propagate and change data stored at the node accordingly. In this way, the system only needs to test each new fact against the rules, and only against those rules to which the new fact is relevant, instead of checking each fact against each rule.

2.4.1 Methods of Inference Engine execution

There are two methods of execution for rule based expert systems, forward chaining and backward chaining. And systems that implement both are called hybrid production rule systems.

2.4.2Forward Chaining

This is a data driven and thus reactionary method. When applying forward chaining, the first step is to take the facts in the fact database and see if any combination of these matches all the antecedents (conditions) of one of the rules in the rule database. When all the antecedents of a rule are matched by facts in the database, then this rule is triggered. Usually, when a rule is triggered, it is then fired, which means its conclusion is added to the facts database.

2.4.3 Backward Chaining

This method is goal driven, meaning that we start with a conclusion which the engine tries to satisfy. An inference engine using backward chaining would search the inference rules until it finds one which has a then clause that matches a desired goal. If the if clause of that inference rule is not known to be true, then it is added to the list of goals. Searches for sub goal conclusions begin, in hopes that, that will help satisfy some part of the current goal. It continues this process until either the initial conclusion is proven or there are no more sub goals.

2.5 Expert system shells

Expert systems can be built that contain all the useful methods without any domain specific knowledge. These systems are called skeletal systems, shells or Artificial intelligence tools. The interpreter is separated from the domain-specific knowledge and thus creating a system that could be used to construct new expert systems by adding new knowledge corresponding to the new problem domain.

Examples of shells include CLIPS, eGanges, OPS5, ART, JESS, and Eclipse.

2.6 Systems currently in use

2.6.1 Expert System for HIV/AIDS information

The above expert system was created under the motivation of a Microsoft sponsored project called IHISM, which aims to contribute to the digital divide by developing an HIV and AIDS public information portal accessible through mobile phones [10].

The Expert system was tailored made with reference to Botswana, according to UNAIDS estimates, HIV/AIDS has affected every segment of Botswana society and one-third of Botswana’s sexually-active population between the ages of 15 and 49 (out of a total population of 1.5 million) are infected with the virus, which is the highest rate in the world [11].

The information service portal would allow the public to request for information on topics related to HIV and AIDS such as descriptions, infection, testing, counselling and support, opportunistic diseases and paediatric care etc. The portal represents this information in the form of Frequently Asked Questions (FAQ) service where the user inputs a query on any of the subjects.

The system is meant to act as an online ‘expert’ in HIV and AIDS information such that, some information may have to be derived through inference as opposed to simple data retrieval. The system is to accept as input a FAQ from the user and provide the most relevant answer to the question.

Challenges of the system:

Users may ask the questions differently in pursuit of the same answer

System should be able to systematically analyse the questions and provide an appropriate answer

System should be able to determine the various forms in which a typical FAQ question could be mapped to the relevant answer.

Participants agreed that the expert system was not only easy to use

2.6.2 A Self-Learning Fuzzy Discrete Event System for HIV/AIDS Treatment Regimen Selection

The HI virus mutates often and so a patient has to be frequently changing their medication course. And because of the strict drug adherence guidelines, it therefore becomes desirable to have a treatment- decision support system that is capable of self-learning.

Basing on the fuzzy discrete event system (FDES) theory, a self-learning HIV/AIDS regimen selection system for the initial round of combination antiretroviral therapy, which is one of the most complex therapies in medicine, was developed [12].

The system consists of a treatment objectives classifier, fuzzy finite state machine models for treatment regimens, and a genetic-algorithm-based optimizer. System focuses on the four historically popular regimens with 32 associated treatment objectives involving the four most important clinical variables (potency, adherence, adverse effects, and future drug options).

Advantages of the A Self-Learning Fuzzy Discrete Event System for HIV/AIDS Treatment Regimen Selection:

Higher flexibility and scalability

Easier knowledge upgrade for accommodating fast treatment strategy evolution with minimal system modification.

Challenges of the A Self-Learning Fuzzy Discrete Event System for HIV/AIDS Treatment Regimen Selection:

Patient-specific medical simulation raises several moral, ethical and policy questions that need to be answered before the methodologies can be put to widespread use.

2.6.3 A grid-based HIV expert system

This system is for physicians to provide an adaptive interactive advice on treatment applied to drug resistant HI virus. Its knowledge base comprises of distributed data from infectious disease patient databases, literature on in-vitro and in-vivo pharmaceutical data, mutation databases, clinical trials, simulations and medical expert knowledge.

The research uses a variety of statistical and numerical methods to identify relationships between HIV genetic sequences and antiviral resistance to investigate consistency of results. Access to and integration of data is done through existing Internet servers and emerging grid-based frameworks like Globus [13].

Advantages of the grid-based HIV expert system:

Cellular automata-based simulations are used to predict the drug behaviour overtime

Limitations of grid-based HIV expert system:

Little data privacy. Sensitive clinical information is often kept on highly secure hospital networks

2.6.4 HIVPCES: a WWW-based HIV patient care expert system

Diagnosing HIV-patients and prescribing the correct drug regimen can be a complex task whose outcome is dependent on a large number of variables. The cost of an incorrectly administered drug even for a very short time can be enormous; the HIV virus has specific drugs that can manage its growth at different levels of its life cycle.

HIVPCES is a WWW-based HIV patient care expert system. It is an interactive expert system to diagnose HIV patients, and is managed centrally and accessed either as part of an intranet, or as an Internet site.781273

The user interface has been carefully designed to provide a high-level of interaction and therefore improve some of the current limitations of Web applications. The system comprises three modules:

(1) A patient self-monitoring personal diary, to create a follow-up patient record;

(2) A data analysis and visualisation tool; and

(3) A section to allow patients to ask for advising and remote doctor support. abstract

Advantages of a WWW-based HIV patient care expert system:

Provides health professionals with new means for tele-monitoring and tele-caring patients.

Limitations of a WWW-based HIV patient care expert system:

Low system security

Users’ anonymity features are required but hard to incorporate in this clinical domain.

2.7 Outline of proposed system

In the vast world of medical expert systems there is little attention given to HIV /AIDS and when the topic does get acknowledged, little focus is put into the treatment and much more attention on the common FAQs about the virus.

This system aims to center on HIV/AIDS suffering patients and offer advice on supplementary natural treatments such as herbal medicines that these patients can use. Unlike some of the current existing systems, which look at drug adherence plan, i.e. narrowing the users down to only, those on the HAART program, the proposed system can be used by patients whose CD4 count has not yet plummeted therefore allows the patient to have a informed decision on how to maintain a healthy life and have a boosted immune system.

Proposed system will offer information on particular herbs, that is, the name, healing effects and the contra-indications and explanations for every herb it advises.

Advantages of proposed system:

Caters for both physicians and patients

Caters for patients not yet on the HAART program, thus serves a wider user range

Knowledge base is an integrated pool of various expert views therefore each answer supplied is about 85%

System is a web based application, which is easily accessible from any computer or location with Internet access.

2.8 Conclusion

The collected information above was used for the design and methodology of the proposed system. This chapter reviewed the domain in study i.e. HIV/AIDS, expert systems and a review of systems currently in existence. The following chapters of the document consist of the integration and modification of the gathered literature.

Herbs have been used extensively in hopes of improving immune response and reducing symptoms. No known herbal remedy has been shown to cure AIDS or even reduce chances of AIDS-related infections. Still, some herbs can be worth trying if used safely and in consultation with a qualified practitioner who not only understands herbs but also has experience treating AIDS and HIV infection.

Immunity-boosting herbs (such as Astragalus, Echinacea, and Ginkgo) may help revive an ailing immune system, and certain herbs (such as Garlic) may help battle bacteria and viruses. Deglycyrrhizinated licorice can soothe the mouth and throat ulcers that often accompany full-blown AIDS.

Unfortunately, there is no known scientific explanation yet, for how herbs have these ‘powers’ in treating AIDS and the only information available about how useful herbal treatments and remedies can be, is based on the knowledge gained from people living with HIV/AIDS. This means that not all herbs and remedies have the same effect on all people.

Some communities have their own knowledge of health and nutrition, based on local traditions and culture. This may complicate the administration of herbal remedies from region to region, as the fundamental factor is now depending whether the patient is willing to cross cultures in order to obtain treatment.

In some extreme cases, any external medical recommendations that a patient may receive is compared with their cultural practices and the recommendations of their traditional healers. Patients will only take action if the recommendations they receive appear to make sense and provide some benefit.

Ironically, some traditional beliefs and food practices may not be useful at all, judging that a herb like Garlic root should work whether the patient is of Chinese or African descent. Patients with HIV/AIDS often become frustrated with management of the disease and are willing to try anything in the hope of staying healthy and living longer.

One of the greatest disadvantages is that HIV/AIDS is not a traditional illness and so far, there is no hard evidence to believe that traditional medicines or herbal remedies can treat HIV and cure AIDS. However, certain herbal medicines may help to treat many of the symptoms of opportunistic infections that are part of AIDS. While some of these medicines may be undoubtedly helpful, others may be dangerous as they may do more harm than good. This happens when the patient mixes pharmaceutical drugs and herbs resulting in contra-indications or when they take certain foods that should be otherwise avoided.

The notion that herbal medicines are natural and therefore safe is as widespread as it is misleading. Some of these remedies have been associated with severe adverse effects caused by the toxicity of the herbal ingredients. Others may cause problems because of contamination or adulteration [9].

Herbs and spices should be used in moderate amounts. Exceeding these amounts may cause problems and have a toxic effect; moreover, the function of the herbs and spices will not be increased. Herbs do not replace healthy eating and should not be used in place of a healthy and balanced diet but they do retain the body’s natural pH (alkaline) and this in turn, as discussed before, forces the microzymes to stop mutating into bacteria, viruses and funguses that cause opportunistic infections.

2.1.7 Advantages of Herbal Treatment:

On general note, Herbal therapies seek to boost patients’ immune systems, inhibit opportunistic infections, alleviate symptoms, and inhibit HIV itself.

Herbal medicines are very cheap in comparison to the conventional form of medication

Herbal medicine helps the body to maintain its natural pH, which is alkaline; this in turn starves and inhibits all adverse microzymes from growing or mutating.

Herbal medicines can be consumed without the aid of any kind of prescription, although a herbal or medical practitioner has to be consulted prior

Herbal medicines are known to be more productive in comparison to other forms of medication in curing certain conditions.

Herbal medicines offer long lasting benefits in terms of overall wellness.

In certain situations, Herbs are considered a possible means to minimize drug side effects.

Unlike with the convectional highly active antiretroviral therapy (HAART), herbs do not need to work in combination in order to get effective results

Herbs are readily available and once a patient knows which herb to use, he/she can grow their own.

2.1.8 Disadvantages of Herbal Treatment:

Curing period is usually longer in comparison to conventional medication

Drug-interactions can be hazardous to a patient ,if they decide to mix herbs and drugs

Herbal medicines are known to be ineffective against serious ailments

Herbal medicines are taken without prescription which means that in some cases, individual might be undergoing a trial and error process with their medication.

Herbal medicines can cause allergic reactions in some cases

Herbal medicines will not eliminate the HI virus out of the body

Most governments do not approve of any kind of herbal medication. It’s usually consumed upon the person’s own risk, and when it comes to branded herbal supplements one can’t expect any kind of quality assurance

2.2 Expert Systems and their use on the Internet

2.2.0 Expert systems

An expert system is a computer program that incorporates concepts derived from experts in a field, uses the available information, heuristics and inference to suggest solutions to problems in that particular discipline or give advice.

An expert system should have good decision making, this is strongly dependent on various capabilities that include the effective acquisition, storage, distribution and sophisticated use of the human experts in the field in question.

The most widely used way of representing domain knowledge in expert systems is as a set of production rules which is also how humans generally infer decisions. Expert systems were made to provide knowledge and advice to a larger number of users than one user. An Expert system can be viewed as a teaching tool because it is equipped with the unique features which allow the users to ask questions on how, why and what format, expert systems also allow automation of many tasks that could not be effectively handled by human experts.

In addition, an Expert system attempts to emulate how a human expert solves a problem, mostly by the manipulation of symbols instead of numbers. As a result because of the low cost per user and automation of numerous tasks ,expert system making has become very attractive and in the long run is much cheaper than getting human expert advice, its development is however relatively costly but its operation is easy and quite cheap.

Maintenance is easy as well because once an expert system is developed it is simple to add new information to the knowledge base and new rules can be developed.

2.2.1 Advantages of Expert systems

Availability: The expert system is always available 24 hours a day and will on no account tire

Can capture scarce expertise, collected from a number of experts and integrate their opinions.

Consistency: The computer does not make common futile human mistakes such as forgetting, getting drunk or strike when it is most needed.

Data can be kept up-to-date.

Efficiency: Expert systems have an increased output and productivity as well as decreased decision making time.

Flexibility: Expert systems can operate in hazardous environments. They can also work with incomplete or uncertain information.

Scalability: The system can be used at a distance over a network therefore can reach a large population.

The computer can store far more information than a human expert.

2.2.2 Disadvantages of Expert systems

Expertise can be hard to extract from humans

Expert system users have natural cognitive limits (therefore can not perform as perfectly as a human)

Experts’ vocabulary is often limited and highly technical

Expert systems may not be able to arrive at valid conclusions and sometimes produce incorrect recommendations

Knowledge is not always readily available

Lack of trust by end-users

Most experts have no independent means to validate their conclusions

2.3 Structure of Expert systems

A typical expert system consists of:

A knowledge base; this contains the specific domain knowledge that is used by an expert to derive conclusions from facts

The inference engine, which is responsible for using the rules and facts to derive conclusions whether it is through forward, backward chaining or a combination of both.

An explanation system, which provides information to the user about how the inference engine arrived at its conclusions

A fact database, which contains the case-specific data that are to be used in a particular case to derive a conclusion and

A User interface, which provides access to the inference engine, the explanation system, and the knowledge-base editor.

KnowledgeBase

Fact

Database

Expert System Shell

Inference

Engine

Knowledge

Base Editor

Explanation

System

User Interface

User

Figure2.1 A basic structure of an Expert System.

An Expert System can be rule-based, frame based or both. In a rule-based system, the knowledge base is a database of rules. Rule-based systems are computer systems that use rules to provide recommendations or diagnoses, or to determine a course of action in a particular situation or to solve a particular problem.

Its line of reasoning or the inference engine technique can be forward chaining, backward chaining, or a combination of both and the Rete algorithm.

2.4 Inference Engine

The knowledge in the knowledge base is used for reasoning and inferring conclusions. An inference rule is an abstract structure that contains a set of rules that mathematically delineates a (usually infinite) set of finite length strings over a (usually finite) alphabet. It is a two part structure using First Order Logic for knowledge representation.

If

<conditions>

then

<actions>

The brain of expert system is the inference engine which is generally a large number of rules and facts. The inference engine matches facts and data, which is in the fact database against the inference rules to infer conclusions which result in actions. The process of matching the new or existing facts against inference rules is called Pattern matching.

Pattern matching in the inference engine can use any of the following algorithms:

Linear

Rete

Treat

Leaps

Most of the rule engines under study implement and extend the Rete algorithm. Leaps is also used widely but is questionable due to poor maintenance. Rete based engines have proprietary enhancements to the Rete algorithm like RetePlus, Rete III and ReteOO.

The Rete algorithm is responsible for ensuring that there is a clear distinction between rules and facts in the database. This algorithm takes the form of a network, with nodes and paths. Each path from the root node to a leaf in the tree represents the left-hand side of a rule. Each node stores details of which facts have been matched by the rules at that point in the path.

In situations where new data or facts are added, it means the Rete algorithm will propagate and change data stored at the node accordingly. In this way, the system only needs to test each new fact against the rules, and only against those rules to which the new fact is relevant, instead of checking each fact against each rule.

2.4.1 Methods of Inference Engine execution

There are two methods of execution for rule based expert systems, forward chaining and backward chaining. And systems that implement both are called hybrid production rule systems.

2.4.2Forward Chaining

This is a data driven and thus reactionary method. When applying forward chaining, the first step is to take the facts in the fact database and see if any combination of these matches all the antecedents (conditions) of one of the rules in the rule database. When all the antecedents of a rule are matched by facts in the database, then this rule is triggered. Usually, when a rule is triggered, it is then fired, which means its conclusion is added to the facts database.

2.4.3 Backward Chaining

This method is goal driven, meaning that we start with a conclusion which the engine tries to satisfy. An inference engine using backward chaining would search the inference rules until it finds one which has a then clause that matches a desired goal. If the if clause of that inference rule is not known to be true, then it is added to the list of goals. Searches for sub goal conclusions begin, in hopes that, that will help satisfy some part of the current goal. It continues this process until either the initial conclusion is proven or there are no more sub goals.

2.5 Expert system shells

Expert systems can be built that contain all the useful methods without any domain specific knowledge. These systems are called skeletal systems, shells or Artificial intelligence tools. The interpreter is separated from the domain-specific knowledge and thus creating a system that could be used to construct new expert systems by adding new knowledge corresponding to the new problem domain.

Examples of shells include CLIPS, eGanges, OPS5, ART, JESS, and Eclipse.

2.6 Systems currently in use

2.6.1 Expert System for HIV/AIDS information

The above expert system was created under the motivation of a Microsoft sponsored project called IHISM, which aims to contribute to the digital divide by developing an HIV and AIDS public information portal accessible through mobile phones [10].

The Expert system was tailored made with reference to Botswana, according to UNAIDS estimates, HIV/AIDS has affected every segment of Botswana society and one-third of Botswana’s sexually-active population between the ages of 15 and 49 (out of a total population of 1.5 million) are infected with the virus, which is the highest rate in the world [11].

The information service portal would allow the public to request for information on topics related to HIV and AIDS such as descriptions, infection, testing, counselling and support, opportunistic diseases and paediatric care etc. The portal represents this information in the form of Frequently Asked Questions (FAQ) service where the user inputs a query on any of the subjects.

The system is meant to act as an online ‘expert’ in HIV and AIDS information such that, some information may have to be derived through inference as opposed to simple data retrieval. The system is to accept as input a FAQ from the user and provide the most relevant answer to the question.

Challenges of the system:

Users may ask the questions differently in pursuit of the same answer

System should be able to systematically analyse the questions and provide an appropriate answer

System should be able to determine the various forms in which a typical FAQ question could be mapped to the relevant answer.

Participants agreed that the expert system was not only easy to use

2.6.2 A Self-Learning Fuzzy Discrete Event System for HIV/AIDS Treatment Regimen Selection

The HI virus mutates often and so a patient has to be frequently changing their medication course. And because of the strict drug adherence guidelines, it therefore becomes desirable to have a treatment- decision support system that is capable of self-learning.

Basing on the fuzzy discrete event system (FDES) theory, a self-learning HIV/AIDS regimen selection system for the initial round of combination antiretroviral therapy, which is one of the most complex therapies in medicine, was developed [12].

The system consists of a treatment objectives classifier, fuzzy finite state machine models for treatment regimens, and a genetic-algorithm-based optimizer. System focuses on the four historically popular regimens with 32 associated treatment objectives involving the four most important clinical variables (potency, adherence, adverse effects, and future drug options).

Advantages of the A Self-Learning Fuzzy Discrete Event System for HIV/AIDS Treatment Regimen Selection:

Higher flexibility and scalability

Easier knowledge upgrade for accommodating fast treatment strategy evolution with minimal system modification.

Challenges of the A Self-Learning Fuzzy Discrete Event System for HIV/AIDS Treatment Regimen Selection:

Patient-specific medical simulation raises several moral, ethical and policy questions that need to be answered before the methodologies can be put to widespread use.

2.6.3 A grid-based HIV expert system

This system is for physicians to provide an adaptive interactive advice on treatment applied to drug resistant HI virus. Its knowledge base comprises of distributed data from infectious disease patient databases, literature on in-vitro and in-vivo pharmaceutical data, mutation databases, clinical trials, simulations and medical expert knowledge.

The research uses a variety of statistical and numerical methods to identify relationships between HIV genetic sequences and antiviral resistance to investigate consistency of results. Access to and integration of data is done through existing Internet servers and emerging grid-based frameworks like Globus [13].

Advantages of the grid-based HIV expert system:

Cellular automata-based simulations are used to predict the drug behaviour overtime

Limitations of grid-based HIV expert system:

Little data privacy. Sensitive clinical information is often kept on highly secure hospital networks

2.6.4 HIVPCES: a WWW-based HIV patient care expert system

Diagnosing HIV-patients and prescribing the correct drug regimen can be a complex task whose outcome is dependent on a large number of variables. The cost of an incorrectly administered drug even for a very short time can be enormous; the HIV virus has specific drugs that can manage its growth at different levels of its life cycle.

HIVPCES is a WWW-based HIV patient care expert system. It is an interactive expert system to diagnose HIV patients, and is managed centrally and accessed either as part of an intranet, or as an Internet site.781273

The user interface has been carefully designed to provide a high-level of interaction and therefore improve some of the current limitations of Web applications. The system comprises three modules:

(1) A patient self-monitoring personal diary, to create a follow-up patient record;

(2) A data analysis and visualisation tool; and

(3) A section to allow patients to ask for advising and remote doctor support. abstract

Advantages of a WWW-based HIV patient care expert system:

Provides health professionals with new means for tele-monitoring and tele-caring patients.

Limitations of a WWW-based HIV patient care expert system:

Low system security

Users’ anonymity features are required but hard to incorporate in this clinical domain.

2.7 Outline of proposed system

In the vast world of medical expert systems there is little attention given to HIV /AIDS and when the topic does get acknowledged, little focus is put into the treatment and much more attention on the common FAQs about the virus.

This system aims to center on HIV/AIDS suffering patients and offer advice on supplementary natural treatments such as herbal medicines that these patients can use. Unlike some of the current existing systems, which look at drug adherence plan, i.e. narrowing the users down to only, those on the HAART program, the proposed system can be used by patients whose CD4 count has not yet plummeted therefore allows the patient to have a informed decision on how to maintain a healthy life and have a boosted immune system.

Proposed system will offer information on particular herbs, that is, the name, healing effects and the contra-indications and explanations for every herb it advises.

Advantages of proposed system:

Caters for both physicians and patients

Caters for patients not yet on the HAART program, thus serves a wider user range

Knowledge base is an integrated pool of various expert views therefore each answer supplied is about 85%

System is a web based application, which is easily accessible from any computer or location with Internet access.

2.8 Conclusion

The collected information above was used for the design and methodology of the proposed system. This chapter reviewed the domain in study i.e. HIV/AIDS, expert systems and a review of systems currently in existence. The following chapters of the document consist of the integration and modification of the gathered literature.

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