Summary of Wispermed at “discharge Me!”: Advancing Text Generation in Healthcare with Large Language Models, Dynamic Expert Selection, and Priming Techniques on Mimic-iv, by Hendrik Damm et al.
WisPerMed at “Discharge Me!”: Advancing Text Generation in Healthcare with Large Language Models, Dynamic Expert Selection, and Priming Techniques on MIMIC-IV
by Hendrik Damm, Tabea M. G. Pakull, Bahadır Eryılmaz, Helmut Becker, Ahmad Idrissi-Yaghir, Henning Schäfer, Sergej Schultenkämper, Christoph M. Friedrich
First submitted to arxiv on: 18 May 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Machine Learning (cs.LG)
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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 paper explores the use of state-of-the-art language models to automate generating sections of Discharge Summaries from the MIMIC-IV dataset, aiming to reduce clinicians’ administrative workload and improve documentation accuracy. Various strategies were employed, including few-shot learning, instruction tuning, and Dynamic Expert Selection (DES), to develop models capable of generating the required text sections. The study achieved promising results, with the DES method achieving an overall score of 0.332 in a competition, surpassing single-model outputs. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper uses special language models to help doctors write discharge summaries faster and more accurately. Doctors often spend too much time writing these summaries, which can take away from time they could be spending with patients. The study tested different ways of using these language models to generate the discharge summary sections. The best method used was called Dynamic Expert Selection (DES). This method let the computer choose the best words and sentences to use in the discharge summary. The results were very promising, showing that this method can help doctors write discharge summaries more quickly and accurately. |
Keywords
» Artificial intelligence » Few shot » Instruction tuning
