| Medmcqa: A large-scale multi-subject multi-choice dataset for medical domain question answering A Pal, LK Umapathi, M Sankarasubbu Conference on health, inference, and learning, 248-260, 2022 | 431 | 2022 |
| Multi-label text classification using attention-based graph neural network A Pal, M Selvakumar, M Sankarasubbu arXiv preprint arXiv:2003.11644, 2020 | 140 | 2020 |
| Med-halt: Medical domain hallucination test for large language models A Pal, LK Umapathi, M Sankarasubbu arXiv preprint arXiv:2307.15343, 2023 | 131 | 2023 |
| BioELECTRA: pretrained biomedical text encoder using discriminators KR Kanakarajan, B Kundumani, M Sankarasubbu Proceedings of the 20th workshop on biomedical language processing, 143-154, 2021 | 131 | 2021 |
| Federated learning for healthcare domain-pipeline, applications and challenges M Joshi, A Pal, M Sankarasubbu ACM Transactions on Computing for Healthcare 3 (4), 1-36, 2022 | 128 | 2022 |
| Pay attention to the cough: Early diagnosis of COVID-19 using interpretable symptoms embeddings with cough sound signal processing A Pal, M Sankarasubbu Proceedings of the 36th Annual ACM Symposium on Applied Computing, 620-628, 2021 | 96 | 2021 |
| Openbiollms: Advancing open-source large language models for healthcare and life sciences A Pal, M Sankarasubbu Hugging Face, 2024 | 43 | 2024 |
| Gemini goes to med school: exploring the capabilities of multimodal large language models on medical challenge problems & hallucinations A Pal, M Sankarasubbu Proceedings of the 6th Clinical Natural Language Processing Workshop, 21-46, 2024 | 30 | 2024 |
| Saama AI research at SemEval-2023 Task 7: exploring the capabilities of Flan-T5 for multi-evidence natural language inference in clinical trial data KR Kanakarajan, M Sankarasubbu Proceedings of the 17th International Workshop on Semantic Evaluation …, 2023 | 17 | 2023 |
| Convolutional neural networks in classifying cancer through DNA methylation S Chatterjee, A Iyer, S Avva, A Kollara, M Sankarasubbu arXiv preprint arXiv:1807.09617, 2018 | 16 | 2018 |
| Data-driven multi-valley dark solitons of multi-component Manakov model using physics-informed neural networks M Jaganathan, TA Bakthavatchalam, M Vadivel, S Murugan, G Balu, ... Chaos, Solitons & Fractals 172, 113509, 2023 | 15 | 2023 |
| Bayesian optimization of Bose-Einstein condensates TA Bakthavatchalam, S Ramamoorthy, M Sankarasubbu, R Ramaswamy, ... Scientific Reports 11 (1), 5054, 2021 | 10 | 2021 |
| Symspell and lstm based spell-checkers for tamil S Murugan, TA Bakthavatchalam, M Sankarasubbu Tamil Internet Conference 11, 2020 | 10 | 2020 |
| Primer on solving differential equations using machine learning techniques TA Bakthavatchalam, S Murugan, S Ramamoorthy, M Sankarasubbu, ... Romanian Reports in Physics 74, 113, 2022 | 7 | 2022 |
| BioSimCSE: BioMedical sentence embeddings using contrastive learning KR Kanakarajan, B Kundumani, A Abraham, M Sankarasubbu Proceedings of the 13th International Workshop on Health Text Mining and …, 2022 | 6 | 2022 |
| Small-bench nlp: Benchmark for small single gpu trained models in natural language processing KR Kanakarajan, B Kundumani, M Sankarasubbu arXiv preprint arXiv:2109.10847, 2021 | 6 | 2021 |
| Saama research at mediqa 2019: Pre-trained biobert with attention visualisation for medical natural language inference KR Kanakarajan, S Ramamoorthy, V Archana, S Chatterjee, ... Proceedings of the 18th BioNLP Workshop and Shared Task, 510-516, 2019 | 5 | 2019 |
| Compositional attention networks for interpretability in natural language question answering M Selvakumar, S Ramamoorthy, V Archana, M Sankarasubbu arXiv preprint arXiv:1810.12698, 2018 | 4 | 2018 |
| PHI Scrubber: A Deep Learning Approach MS A Dilip, Kamal Raj K Arxiv.org, 2018 | 4* | 2018 |
| Saama Technologies at BioLaySumm: Abstract based fine-tuned models with LoRA H Kim, KR Kanakarajan, M Sankarasubbu Proceedings of the 23rd Workshop on Biomedical Natural Language Processing …, 2024 | 2 | 2024 |
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