Muse Alpha: AI-based Preliminary Diagnosis for Cognitive Thought Patterns

Abstract: Recent issues of medication misuse and abuse have prompted research into utilizing big data and artificial intelligence to aid psychiatrists in determining medication dosages. Muse Alpha contributes through high-quality data collection, AI-based patient similarity analysis, and a patient-centric conversation approach. This includes the extraction of patterns of negative thoughts, achieving up to 87.5% accuracy in guiding conversations. The goal is to overcome the limitations of brief one to one interactions between doctors and patients, ensuring more accurate medication prescriptions. Discovering patterns of negative thoughts and conveying them visually to the doctor assists in providing an accurate diagnosis of the patient's condition and aids in the precise diagnosis of medication for the patient.

Keywords: Medical System, Artificial Intelligence, Machine Learning, Health Care, Medical Device

DOI: 10.54941/ahfe1004839

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