A LITERATURE SURVEY ON COMPUTING METHODS IN PSYCHIATRIC DISORDER

• Published in: International journal of advanced research in computer science Vol. 8; no. 8; pp. 282 - 286
• Main Author: Jain, Shivangi
• Format: Journal Article
• Language: English
• Published: Udaipur International Journal of Advanced Research in Computer Science 01.09.2017
• Subjects: Accident prevention; Algorithms; Ant colony optimization; Artificial neural networks; Bayesian analysis; Brain; Classification; Data mining; Datasets; Diagnosis; Echocardiography; Format; Genetic algorithms; Health services; Human behavior; Human relations; Medical research; Medical science; Mental disorders; Mental health; Mental health care; Quantitative psychology; Reasoning
• ISSN: 0976-5697; 0976-5697
• DOI: 10.26483/ijarcs.v8i8.4653

Data mining algorithms and its application having different and diverse field. One of the challenging and emerging research fields is medical science. Medical field exhibit many type of data and thus it provide large statically and dynamic data, its relevant Meta data which contains a detail information about the observation made in different scenario. Medical data such as EEG, ECG reports, MRI reports, different lab test reports and other observation which are either in text format or graphical image format derived. These are different sample format describe various symptoms and prevention associate with those symptoms. Genetic activity, genes presence and repetition also gives user activity detail and problems in human body. Mental illness is a type of disease which relate with the mental disorder. It deals in human interaction, its behavior, and its regular and irregular activity. In this stage human sudden start misbehave or extra activities during the particular phase and hence an unpredictable incident may occur. Psychometric disease cases are increasing day by day with different symptoms in human being. These are diseases which occur due to over work pressure, mental activity, some past human life incident or may be the victim of some good or bad incident. It leads to several problems in society, as per well issue with the person who is suffering with the particular disorder. An human interaction and understanding capacity is different than a normal person which keep person separate from the normal society and social life. These disorders also occur sometime very violent and make it very tedious to recover. Psychiatric relate to brain disorder, Mental disorder, irregular work performing in public etc. Diagnosis over the disease is complex and not fixed. In the previous research on the same concern shows that the past data can be analyzed properly and it can further be useful for the precautions. Mental disorder records may leads to several Meta data, report activities observed by hospital or supervision person. A classification over the given symptoms, its action and medical treatment help in diagnosis. Past studies always parts in important role using which further decision can be taken. Mental disorder, mental health, further possibilities can be observed and driven remedy can be discussed. Data classification algorithm makes it possible to classify the normal and abnormal data cases. Hospital release dataset give the information which tends to changes, mental health of previous patients and their best precautions taken to cure them. Different algorithm model is used which help in mining the previous algorithm data rule over the past cases. It enable user to understand past cases, their symptoms, disease occurred and its diagnosis steps taken. Various algorithms such as Genetic algorithm, Naïve bayes, Ant colony optimization, Rule based reasoning (RBR), Case based reasoning (CBR) and Artificial neural network (ANN) is used for psychometric disease finding from the large dataset. In this paper survey of past techniques is performed. This paper also illustrates the work finding and limitation of previous research. An analysis using the real time dataset over the proposed algorithm is left for further work..