Assessing healthcare software built using IoT and LLM technologies

In the fast-paced world of healthcare technology, combining IoT devices with large language models (LLMs) offers a promising path to transform Clinical Decision-Support Systems (CDSS). This Ph.D. project is designed to tap into IoT's extensive data collection ability and LLMs' superior natural language processing skills. It aims to improve clinical decision-making and patient care through a sophisticated DSS that utilizes both technologies' strengths. The project delves into the software engineering challenges and methodologies required to build an effective DSS. It investigates how to smoothly evaluate and integrate IoT and LLMs into healthcare environments, tackling significant issues like data complexity, privacy concerns, and the necessity for high accuracy in medical settings. It underscores the critical role of thorough evaluation and assessment in developing healthcare technologies.