Mostakim, MoinNasim, Hamim IbneTanvir, SifatDas, Stanley MatthewAlam, AshiqulAlvi, Arif Jawad2026-04-202026-04-2020262026-01ID 21141014ID 21301336ID 21301039http://hdl.handle.net/10361/27967Cataloged from PDF version of thesis.Includes bibliographical references (pages 45-46).This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2026.The increasing digitization of healthcare has led to predictive analytics becoming an essential tool for early risk detection and personalized patient care. This project introduces an optimized predictor for Patient Healthcare Records. This is a microservices-driven, AI-based system architected to analyze patient data while maintaining HIPAA (Health Insurance Portability and Accountability Act), ensuring scalability through Dockerized deployment. The system functions through three main phases: (1) Data processing through Optical Character Recognition (OCR), which extracts text and refines patient data from medical records; (2) Health Risk Prediction utilizing a Hidden Markov Model (HMM) for sequential health analysis and Neural Networks for predictive modeling; and finally, (3) Secure storage and Recommendations where the predictions are organized in a structured PostgreSQL database and accessed via a web/mobile platform built with HTML and CSS. This design guarantees effective, privacy-conscious, and AI-enabled healthcare analytics, delivering real-time insights for healthcare professionals and providing them with a streamlined, scalable, and secure method for health risk prediction, supporting proactive medical decision-making.46 pagesenBRAC University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission.Healthcare digitizationPredictive analyticsPatient health recordsOptical character recognitionHIPAA complianceOptical character recognition device industry.Medical informatics.Health insurance continuation coverage.Thesis