DEVELOPMENT OF DIAGNOSTIC EXPERT SYSTEM
The need for a diagnostic expert system cannot be overemphasized. Infectious viral disease diagnoses are poor in Nigeria and general disease database for accessing patient’s data is unavailable to hospitals and various government agencies. Also with failing health insurance for citizens, relatives of diseased patients are mostly responsible for their family members that are sick. Use of diagnostic expert system will definitely be of greater value in determining and confirming the viral nature of the diseases. Also, the unique attributes of the diagnostic expert system model specified and developed over previous models is the basis for embarking on this research.
Viral infections are collections of diseases caused by viruses that easily attack human, and can be transmitted quickly through touch/contact, air, saliva, or other intermediaries. Therefore, the symptoms caused by infectious viral infections need to be known by medical practitioner. By knowing the symptoms experienced by patients, health worker can immediately find out the disease that is suffered and the prevention, so that the disease suffered by the patient can be treated immediately.
The role of medical practitioner in dealing with dangerous viral infections is necessary but often collides with the limited number of medical experts while those that need to be handled are quite a lot. To reduce this limitation, an expert system is needed.
Outbreaks of infectious diseases are occurring with increasing frequency and unpredictability. The rapid development and deployment of diagnostics that can accurately and quickly identify pathogens as part of epidemic preparedness is needed now for the COVID-19 pandemic.
The expert system application can be a medium of information on capabilities, knowledge, and facilities (based on symptoms or complaints) for health workers in diagnosing viral infections in patients. The application of this expert system uses the certainty factor method that provides a level of trust in the results of the diagnoses of diseases suffered by users. The output from this expert system is not the result of the user's disease diagnosis. The output of this expert system can be used as input or advice for medical experts. The final decision about a patient's illness is the authority of a medical expert.
This will present a sustainable model for a global network of country-owned biobanks with standardized methods for collection, characterization, and archiving of specimens and pathogens to facilitate and accelerate diagnostics development and evaluation for COVID-19 and other diseases of epidemic potential.
- Prevent the spread of misinformation and inspire individuals to protect themselves and their communities, including through information campaigns and behavioral nudges.
An expert system is one important part of artificial intelligence that can mimic human reasoning processes. Expert systems can be used to help diagnose diseases, in this case, viral infections in patients. The expert system diagnoses by tracking the symptoms of each patient, matching them with existing rules, and producing a diagnosis based on the knowledge base. The purpose of this research is to design and make an application system expert diagnosis of infectious viral infections in patients whose results can show the disease suffered by patients, the value of the level of trust from the results of the diagnosis, and suggestions for solutions that can be given to sufferers.
- Concept: An idea being explored for its feasibility to build a product, service, or business model based on that idea.
The aim of this study is to develop a diagnostic expert system that will be useful in diagnosing infectious viral disease(s) in patients by health workers. The specific objectives of the work are to;
extract data from infectious viral disease control database;
classify diseases according to symptoms;
Implement a functional system
Evaluate the system
- A new business model or process that relies on technology to be successful
An expert system is a computer-based system that uses knowledge, facts and reasoning techniques in solving problems that can usually only be solved by an expert in the field.
In general, expert systems are systems that try to adopt human knowledge to computers that are designed to model problem-solving abilities like an expert. With this expert system, even ordinary people can solve the problem or simply find quality information that can only be obtained with the help of experts in their fields. This expert system will also be able to assist the activities of experts as assistants who are experienced and have the required knowledge.
- Artificial Intelligence / Machine Learning
- Biotechnology / Bioengineering
- Internet of Things
- Software and Mobile Applications
- Women & Girls
- Infants
- Children & Adolescents
- Elderly
- Rural
- Peri-Urban
- Urban
- Poor
- Low-Income
- Middle-Income
- Refugees & Internally Displaced Persons
- Minorities & Previously Excluded Populations
- Persons with Disabilities
- 3. Good Health and Well-being
- 9. Industry, Innovation and Infrastructure
- 11. Sustainable Cities and Communities
- 17. Partnerships for the Goals
500 ,
50000,
5000,000
Expert systems are widely used to diagnose diseases especially in health areas and other disciplines. This is a computer system that nearly earns the decision making ability of a human expert. The goal of designing an expert system is to solve a complex problem by reasoning with knowledge rather than by conventional procedural codes. An expert system consists of two parts namely, the inference engine and the knowledge base. Knowledge base of an expert system dedicated to represent the knowledge about a domain. Various knowledge representation schemas such as Propositional Logic (PL), First Order Logic (FOL), Fuzzy Logic (FL), Frames, Semantic Net, Case Based Reasoning and Bayesian Belief Network are widely used to build the knowledge base of an expert system. Both PL and FOL are used to acquire assertive knowledge and hence, unable to represent various types of uncertainties. Semantic Net is a directed or undirected graph, which represents semantic relations between concepts but not the uncertainty. Bayesian Belief Network or BNN is a directed acyclic graph representing the facts using conditional probability.
- For-profit, including B-Corp or similar models
5-10
The need for a diagnostic expert system cannot be overemphasized. Infectious viral disease diagnoses are poor in Nigeria and general disease database for accessing patient’s data is unavailable to hospitals and various government agencies. Also with failing health insurance for citizens, relatives of diseased patients are mostly responsible for their family members that are sick. Use of diagnostic expert system will definitely be of greater value in determining and confirming the viral nature of the diseases. Also, the unique attributes of the diagnostic expert system model specified and developed over previous models is the basis for embarking on this research.
Outbreaks of infectious diseases are occurring with increasing frequency and
unpredictability. The rapid development and deployment of diagnostics
that can accurately and quickly identify pathogens as part of
epidemic preparedness is needed now for the COVID-19 pandemic. WHO
has developed a global research and innovation forum to facilitate,
accelerate, and deepen research collaboration among countries and
funders. Great progress has been made in the past decade, but access
to specimens remains a major barrier for the development and
evaluation of needed quality diagnostics. This will present a
sustainable model for a global network of country-owned biobanks with
standardized methods for collection, characterization, and archiving
of specimens and pathogens to facilitate and accelerate diagnostics
development and evaluation for COVID-19 and other diseases of
epidemic potential.
- Organizations (B2B)
To impart lives in term of providing solutions to health challenges via the use of technology,artificial intelligence and diagnosis
- Human Capital (e.g. sourcing talent, board development, etc.)
- Business model (e.g. product-market fit, strategy & development)
- Financial (e.g. improving accounting practices, pitching to investors)
- Legal or Regulatory Matters
- Public Relations (e.g. branding/marketing strategy, social and global media)
- Monitoring & Evaluation (e.g. collecting/using data, measuring impact)
- Product / Service Distribution (e.g. expanding client base)
- Technology (e.g. software or hardware, web development/design, data analysis, etc.)
To impart lives in term of providing solutions to health challenges via
the use of technology,artificial intelligence and diagnosis
My potential partners could include organizations such as MIT faculty or initiatives, or Solve Members and Canadian Health Research Corporation.
They can be of help in Human Resources,IT , Financial and Application development.
- Yes, I wish to apply for this prize
To impart lives in term of providing solutions to health challenges via
the use of technology,artificial intelligence and diagnosis
- Yes, I wish to apply for this prize
To impart lives in term of providing solutions to health challenges via
the use of technology,artificial intelligence and diagnosis
- Yes, I wish to apply for this prize
To impart lives in term of providing solutions to health challenges via
the use of technology,artificial intelligence and diagnosis
- Yes, I wish to apply for this prize
To impart lives in term of providing solutions to health challenges via
the use of technology,artificial intelligence and diagnosis to build diagnostic expert system
- Yes
To impart lives in term of providing solutions to health challenges via
the use of technology,artificial intelligence and diagnosis to build diagnostic expert system