Summary of Can Artificial Intelligence Generate Quality Research Topics Reflecting Patient Concerns?, by Jiyeong Kim et al.
Can Artificial Intelligence Generate Quality Research Topics Reflecting Patient Concerns?
by Jiyeong Kim, Michael L. Chen, Shawheen J. Rezaei, Mariana Ramirez-Posada, Jennifer L. Caswell-Jin, Allison W. Kurian, Fauzia Riaz, Kavita Y. Sarin, Jean Y. Tang, Steven M. Asch, Eleni Linos
First submitted to arxiv on: 15 Nov 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Information Retrieval (cs.IR)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The proposed framework uses natural language processing (NLP) and artificial intelligence (AI) to generate research ideas prioritizing important patient issues. The framework leverages patient portal messages from 614,464 patients with breast or skin cancer to define clinical concerns and then generates topics using ChatGPT-4o AI. The research topics are evaluated by six oncologists and dermatologists for significance and novelty. The results show that AI-generated topics can be highly significant and novel, guiding future directions in patient-centered health research. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary A new way of doing medical research is being developed. It uses computers to look at messages from patients with breast or skin cancer. These messages help the computers understand what’s important to the patients and then suggest ways for researchers to study these issues. The suggestions are checked by doctors who specialize in treating these cancers, and many of them are very good ideas that could lead to new discoveries. |
Keywords
» Artificial intelligence » Natural language processing » Nlp
