Papers by Nirmala Pudota
MedCodER: A Generative AI Assistant for Medical Coding (2025.naacl-industry)
Copied to clipboard
Krishanu Das Baksi, Elijah Soba, John J Higgins, Ravi Saini, Jaden Wood, Jane Cook, Jack I Scott, Nirmala Pudota, Tim Weninger, Edward Bowen, Sanmitra Bhattacharya
| Challenge: | Medical coding is time-consuming and error-prone due to large label space, lengthy text inputs, and the absence of supporting evidence annotations. |
| Approach: | They propose a Generative AI framework for automatic medical coding that leverages extraction, retrieval, and re-ranking techniques as core components. |
| Outcome: | The proposed framework outperforms existing methods on the International Classification of Diseases (ICD) code prediction scale. |