Papers by Saeel Nachane
Few shot chain-of-thought driven reasoning to prompt LLMs for open-ended medical question answering (2024.findings-emnlp)
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Saeel Nachane, Ojas Gramopadhye, Prateek Chanda, Ganesh Ramakrishnan, Kshitij Jadhav, Yatin Nandwani, Dinesh Raghu, Sachindra Joshi
| Challenge: | Large Language models (LLMs) are increasingly utilized in the healthcare sector for query-related tasks. |
| Approach: | They propose a modified version of the MedQA-USMLE dataset, named MEDQA-OPEN, which contains open-ended medical questions without options to mimic clinical scenarios. |
| Outcome: | The proposed approach outperforms the state-of-the-art 5-shot CoT-based prompt by exploring multiple differential diagnoses and narrowing down to a final diagnosis using MCQ-ELIMINATIVE. |