An AI-based framework for Record-Keeping and Medical History

This paper addresses the challenges encountered in digitizing patient history, particularly in local clinics within developing nations like India. Despite repetitive efforts by the Government of India to promote standardized digitized medical record-keeping through Information and Communication Technologies (ICT), successful adoption remains elusive. To address this issue, the research employs a comprehensive methodology involving habitat studies, interviews, and patient surveys. Through this approach, specific obstacles faced by these clinics are identified, emphasizing the need for understanding user perspectives. The proposed Integrated Framework for Medical Record-Keeping (IFMR) incorporates advanced features such as Transfer Learning and Clinical BERT, aiming to enhance user experience and increase the likelihood of successful adoption. These enhancements contribute to a transformative perspective on medical record-keeping, emphasizing improved healthcare outcomes by providing health disclaimers and alerts to healthcare professionals. The abstract highlights the motivation behind the research, outlines the research method employed, summarizes key results, and concludes with implications for future research and practice.