Potential Applications and Areas of Health-Care Research for ChatGPT and Similar LLMs

Area no.Description
1Models and applications that can leverage multimodal data such as merging language and imaging, for example, highlighting anomalies in a natural way (with language) when reading PET images
2Summary of complex medical histories and records
3Summary of information from medical congresses/clinical trial results
4Structuring/making information interoperable, for example, during medical documentation (20)
5Facilitating clinical documentation such as writing discharge report; once we have structured information, is there really a need for free text? (facts should be communicated reliably and concisely)
6Integration with hospital information systems to incorporate patient data, specifications, and requirements (institutional, payer) and resources (staff capacity, provider)
7Interpretation and explanation of other AI algorithms (1)
8Translation into other languages, with big potential for less frequently used languages for which use of natural language processing was limited in the past
9Translation into patient-comprehensible language, making medical information communication more consumer-friendly
11Relief for nursing staff through automized ward communication
12Medical writing (21)
13Anonymization of clinical text
14Fairness, bias in LLMs
15Human-in-loop and human-centered design of LLM applications
16Chain-of-thought and automated reasoning on LLMs