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Expert or knowledge-based systems are the most common type of AIM (artificial intelligence in medicine) system in routine clinical use. They contain medical knowledge, usually about a very specifically defined task, and are able to reason with data from individual patients to come up with reasoned conclusion. Although there are many variations, the knowledge within an expert system is typically represented in the form of a set of rules. Arthritis is a chronic disease and about three fourth of the patients are suffering from osteoarthritis and rheumatoid arthritis which are undiagnosed and the delay of detection may cause the severity of the disease at higher risk. Thus, earlier detection of arthritis and treatment of its type of arthritis and related locomotry abnormalities is of vital importance. Thus the work was aimed to design a system for the diagnosis of Arthitis using fuzzy logic controller (FLC) which is, a successful application of Zadeh's fuzzy set theory. It is a potential tool for dealing with uncertainty and imprecision. Thus, the knowledge of a doctor can be modelled using an FLC. The performance of an FLC depends on its knowledge base which consists of a data base and a rule base. It is observed that the performance of an FLC mainly depends on its rule base, and optimizing the membership function distributions stored in the data base is a fine tuning process.

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The commenced work deals with the synthesis, characterization and evaluation of biological activities of 4-amino-2,3-dimethyl-1-phenyl-3-pyrazolin-5-one. The synthesis was done by the condensation of aromatic acid chlorides with 4-aminoantipyrine. The structures of synthesized derivatives were elucidated using IR, Mass, H NMR andC NMR spectroscopy, and their UV-Visible and fluorescence properties were studied. The compounds showed significant dual fluorescence. Molecular docking was used to understand the small molecule-receptor protein interaction. The derivatives were screened for their in vitro cytotoxic activity against the reference drug pazopanib on human cervical cancer cell line (SiHa) using MTT assay.