| From "MedMCQA: A Large-scale Multi-Subject Multi-Choice Dataset for Medical domain Question Answering" |
| (Pal et al.), MedMCQA is a "multiple-choice question answering (MCQA) dataset designed to address |
| real-world medical entrance exam questions." The dataset "...has more than 194k high-quality AIIMS & NEET PG |
| entrance exam MCQs covering 2.4k healthcare topics and 21 medical subjects are collected with an average |
| token length of 12.77 and high topical diversity." |
|
|
| The following is an example from the dataset: |
|
|
| Question: In a patient of heart disease antibiotic prophylaxis for dental extraction is: |
| A. Amoxicillin. |
| B. Imipenem. |
| C. Gentamicin. |
| D. Erythromycin. |
| Answer: A |
|
|
| Paper: https://arxiv.org/abs/2203.14371 |
| Code: https://github.com/MedMCQA/MedMCQA |
|
|
| ``` |
| @InProceedings{pmlr-v174-pal22a, |
| title = {MedMCQA: A Large-scale Multi-Subject Multi-Choice Dataset for Medical domain Question Answering}, |
| author = {Pal, Ankit and Umapathi, Logesh Kumar and Sankarasubbu, Malaikannan}, |
| booktitle = {Proceedings of the Conference on Health, Inference, and Learning}, |
| pages = {248--260}, |
| year = {2022}, |
| editor = {Flores, Gerardo and Chen, George H and Pollard, Tom and Ho, Joyce C and Naumann, Tristan}, |
| volume = {174}, |
| series = {Proceedings of Machine Learning Research}, |
| month = {07--08 Apr}, |
| publisher = {PMLR}, |
| pdf = {https://proceedings.mlr.press/v174/pal22a/pal22a.pdf}, |
| url = {https://proceedings.mlr.press/v174/pal22a.html}, |
| abstract = {This paper introduces MedMCQA, a new large-scale, Multiple-Choice Question Answering (MCQA) dataset |
| designed to address real-world medical entrance exam questions. More than 194k high-quality AIIMS & NEET PG |
| entrance exam MCQs covering 2.4k healthcare topics and 21 medical subjects are collected with an average token |
| length of 12.77 and high topical diversity. Each sample contains a question, correct answer(s), and other |
| options which requires a deeper language understanding as it tests the 10+ reasoning abilities of a model across |
| a wide range of medical subjects & topics. A detailed explanation of the solution, along with the above |
| information, is provided in this study.} |
| } |
| ``` |
