A Differential Diagnosis in Medical Field Using SOA and Classifier Techniques: A Review

Recent diagnosis in medical field reveals that the probable causes of failure in patients treatment is the misdiagnosis factor that leads to inadequate treatment of the patients. This paper focuses on the misdiagnosis attribute that if mined properly may produce accurate results. The data obtained in hospitals is vast and contains enormous amount of information. Findings for the patients symptoms is based on the current condition of the patient but in some cases the patients medical history also plays a crucial role. The misdiagnosis attribute is taken into consideration in this paper. The system developed predicts the probability of a disease using an algorithm that combines the key features of neural networks, large memory storage and retrieval and k-NN classifier. Thus diagnosis of a patients ailment can be made effectively using such algorithm.