Artificial Intelligence In Medical Science

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Abstract

Artiﬁcialintelligenceis thehumanlikeintelligence exhibited by machines or software.It is an important part of computer science .The advancement in computer technology has encouraged the researchers to develop software for assisting doctors in making decision without consulting the specialists directly.The software development exploits the potential of human intelligence such as reasoning, makingdecision, learning (byexperiencing) and many others. Artiﬁcial intelligence is not a new concept, yet it has been accepted as a new technology in computer science. It has been applied in many areas such as education, business, medical and manufacturing. This paper explores the potential of artiﬁcial intelligence techniques particularly for web-based medical applications. Keyword : Artiﬁcial intelligence, making decision, web-based medical application. I. INTRODUCTION In most developing countries insufﬁcient of medical specialist has increased the mortality of patients suffered from various diseases.The insufﬁcient of medical specialists will never be overcome within a short period of time. The institutionsofhigherlearningcouldhowever,take an immediate action to produce as many doctors as possible.It is a long procedure to transform a general doctor to specialist. Medical practitioner may not have enough expertise or experience to deal with certain high-risk diseases. However, the waiting time for treatments normally takes a few days, weeks or even months. By the time the patients see the specialist,the diseases may have already spread out. As most of the high-risk disease could only be cured at the early stage, the patients may have to suffer for the rest of their life.

Computer program or software developed by emulating human intelligence could be used to assist the doctors in making decision without consulting the specialists directly. The software was not meant to replace the specialist or doctor, yet it was developed to assist general practitioner and specialist in diagnosing and predicting patient’s condition from certain rules or”experience”.Employing the technology Artiﬁcial Intelligence (AI) techniques in medical applications could reduced the cost, time, human expertise and medical error. Computer program known as Medical Decision-Support System was designed to help health professionals make clinical decision [1].The system deals with medical data and knowledge domain in diagnosing patients conditions as well as recommending suitable treatments for the particular patients. Computer program known as Medical DecisionSupport System was designed to help health Patient-Centred Health Information Systems is a patient centered medical information system developed to assist monitoring, managing and interpret patient’s medical history [2].

The system serves to improve the quality of medical decision-making, increases patient compliance and minimizes iatrogenic disease and medical errors. While diagnosing the patient, doctor can refer to patient’s history record for a history treatment. A prescription of medicine can automatically sent to the dispensary. The advancement in computer technology and communication encourages health-care provider to providehealth-careovertheInternetortelemedicine . Telemedicine can improve access to care, increase health-care quality and reduce the cost . Patients from rural areas can access to the same quality of health-care as those in big city. In general, telemedicine means the use of computer andcommunicationstechnologiestoaugmentthe deliveryofhealth-careservices[3].Theapproach reduces the cost and time for both patients and doctors. This paper discussed about artiﬁcial intelligence in medicine, centralized database,webbased medical diagnosis and prediction, speciﬁcally for medical practitioners.

LITERATURE REVIEW

Modern medicine is faced with the challenge of acquiring, analysing and applying the large amount of knowledge necessary to solve complex clinical problems. The development of medical artiﬁcial intelligence has been related to the development of AI programs intended. to help the clinician in the formulation of a diagnosis, the making of therapeutic decisions and the prediction of outcome. They are designed to support healthcare workers in their every day duties, assisting with tasks.

METHODOLOGY

Artiﬁcial intelligence in medicine. It Produces new tools to support medical decision-making, training and research. Integrates activities in medical, computer, cognitive and other sciences. Centralized database. The patients records are valuable information for the knowledge-based system. The current patients data would enhance and strengthen the validity of the system reasoning [4]. • Web-based medical diagnosis and prediction. Prediction module utilizes neural networks techniques to predict patients illness or conditions based on the previous similar cases. Diagnosis module consists of expert system and fuzzy logic techniques to perform diagnosis tasks. IV. AI IN MEDICAL A. AI IN MEDICINE Experienced Based Medical Diagnostics Systemaninteractivemedicaldiagnosticsystem is accessible through the Internet[5] . Case Based Reasoning (CBR) was employed to utilize the speciﬁc knowledge of previously experienced and concrete problem or cases. The system can be used by patients to diagnose themselves without having to make frequent visit to doctors and as well as medical practitioner to extend their knowledge in domain cases (breast cancer).

B. Centralized database The patients records are valuable information for the knowledge-based system. The current patients data would enhance and strengthen the validity of the system reasoning.This implies that patients information in one system can only be used by that particular system. On the other hand, other systems require another databases for other patients or for the same patients whose records were kept in other databases. Another problem with standalone database is that, the database for the same system in another places would differ as the number of patients using the systems increases.

TELEMEDICINE

Telemedicine is the integration of telecommunications technologies, information technologies, human-machine interface technology and medical care technologies for the purpose of enhancing health care delivery across space and time . deﬁne telemedicine as any instance of medical care occurring via the Internet and using real-time videoteleconferencing equipment as well as more specializedmedicaldiagnosticequipment.In general, telemedicine means the use of computer and communications technologies to augment the delivery of health-care services . Telemedicine can improve access to care, increase health-care quality and reduce the cost . Patients from rural areas can access to the same quality of health-care as those in big city.

D. Fuzzy Expert Systems Fuzzy logic is another branch of artiﬁcial intelligence techniques. It deals with uncertainty in knowledge that simulates human reasoning in incomplete or fuzzy data. applied fuzzy relational inference in medical diagnosis. It was used within the medical knowledgebased system, which is referred to as Clinaid. It deals with diagnostic activity, treatment recommendations and patient’s administration.Fuzzy logic has also been used to predict survival in patients with breast cancer[6].

E. Diagnosis Diagnosis module consists of expert system and fuzzy logic techniques to perform diagnosis tasks. A set of rules will be deﬁned using the patients and patients-disease databases as well as the expert knowledge on the disease domain. Expert system uses the rules to diagnose patient’s illness based on their current conditions or symptoms. In addition, fuzzy logic is integrated to enhance the reasoning when dealing with fuzzy data.

The combination of expert system and fuzzy logic that forms a system could increase the system performance.

RESULT ANALYSIS

Each AI technique has its own strengths and weaknesses.The used of computer and communication tools can change the medical practice into a better implementation. Consolidation in health-care provider will happen by focusing on cost and later on quality of services. Advancement in technology will form a platform for development a better design of telemedicine application. Telephone line and Internet will be the most important tools in medical applications. Centralized medical record helps doctors to improve the quality of treatment and provide a better diagnosis based on patients medical history. In addition, researchers in medical applications could use the data in their investigation of a new medical solution, patient’s management and treatment. fuzzy logic will be suitable techniques for dealing with partial evidence and with uncertainty regarding the effects of proposed interventions. For the prediction tasks, Neural Networks have been proven to produce better results compared to other techniques. Such techniques are worth to explore and integrate in the system for medical diagnosis and prediction.

CONCLUSION

There are many different AI techniques availablewhicharecapableofsolvingavariety of clinical problems.There is compelling evidencethatmedicalAIcanplayavitalrole in assisting the clinician to deliver health care efﬁciently in the 21st century. There is little doubt that these techniques will serve to enhance and complement the ‘medical intelligence’ of the future clinician. fﬁciently in a given space. AI can be applied to perform several types of tasks like diagnosis and prognosis, medical imaging and signal processing, and planning and scheduling. The principles of Genetic algorithms have been used to predict outcome in critically ill patients,lung cancer.The approach reduces the cost and time for both patients and doctors.

REFERENCE

Shortliffe,E.H.(1987).ComputerPrograms to Support Clinical Decision Making. Journal of the American Medical Association, Vol. 258, No. 1. Szolovits, P., Doyle, J., Long, W. J., Kohane, I., and Pauker, S. G. (1994).
Patient- Centred Health Information Systems. Technical Report MIT/LCS/TR-604.Massachusetts Institute of Technology. Chellappa, M. (1995).
Telemedic-Care. NCIT’95: 8’th National Conference Information Technology’95 (16-18 August 1995).
Gabungan Komputer Nasional Malaysia. Manickam, S., and Abidi, S. S. R. (1999).
Experienced Based Medical Diagnostics System Over The World Wide Web (WWW), Proceedings of The First National Conference on Artiﬁcial Intelligence Application In Industry, Kuala Lumpur, pp. 47 – 56.
Shortliffe, E. H., Barnet, G. O., Cimino, J. J., Greenes, R. A. and Patel(2003), InterMed: An Internet-Based Medical Collaboratory,Canada Seker H, Odetayo MO, Petrovic D, Naguib RNG, Bartoli C, Alasio L et al (2002).

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Artificial Intelligence In Medical Science

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