• Anjali Sardesai
• Vilas Kharat
• Pradip Sambarey

The important factor in the medical field is disease-symptom knowledge base and symptom-patient relationship which influences the patients, disease diagnosis. Gynecological symptoms consisting of clinical findings, diagnosis and treatment of a disease involves uncertainty and imprecision. The symptoms narrated by patients lead to similar types with varying degree of occurrence and confirmability. As such, the patients need to be classified with respect to vaguely narrated symptoms. Sanchez [1, 2] introduced a fuzzy relation R between symptom S and Disease diagnosis D which he refers to as medical knowledge which expresses the association between symptoms and disease diagnosis. In fact, the use of compositional rule of inference is being assumed [1,2] to describe the state of a patient in terms of diagnosis, and this very rule is also effectively used in the present research article. In this present paper, the disease-symptom-patient relationship is being used to arrive at disease diagnosis in the initial screening process of differential diagnosis. The output of this initial screening process shows that the disease by which a patient is suffering from as well as the classification of patients, are completely dependent on the narrated symptoms. The paper also analyses the output of an initial screening process with the classification details. Besides other details of the study, it has been concluded that the patients suffering from same disease get classified in similar classes at certain possibility value.

Fuzzy Logic, Max-Min Composition, Similarity Measures, Fuzzy Relational Calculus

"Classification and Analysis of Patients’ diagnosis : A Case Study in Gynecology", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 5, page no.j78-j83, May-2025, Available :http://www.jetir.org/papers/JETIR2505A07.pdf

"Classification and Analysis of Patients’ diagnosis : A Case Study in Gynecology", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 5, page no. ppj78-j83, May-2025, Available at : http://www.jetir.org/papers/JETIR2505A07.pdf