Papers by Robert Tinn
Efficient Diagnosis Assignment Using Unstructured Clinical Notes (2023.acl-short)
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| Challenge: | Electronic phenotyping entails using electronic health records (EHRs) to identify patients with specific clinical outcomes and determine when those outcomes occurred. |
| Approach: | They propose a framework for electronic phenotyping that integrates labeling functions and a disease-agnostic neural network to assign diagnoses to patients. |
| Outcome: | The proposed framework disambiguates hypertension true positives and false positives with a supervised area under the precision-recall curve (AUPRC) of 0.85. |
Exploring the Boundaries of GPT-4 in Radiology (2023.emnlp-main)
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Qianchu Liu, Stephanie Hyland, Shruthi Bannur, Kenza Bouzid, Daniel Castro, Maria Wetscherek, Robert Tinn, Harshita Sharma, Fernando Pérez-García, Anton Schwaighofer, Pranav Rajpurkar, Sameer Khanna, Hoifung Poon, Naoto Usuyama, Anja Thieme, Aditya Nori, Matthew Lungren, Ozan Oktay, Javier Alvarez-Valle
| Challenge: | Recent success of general-domain large language models has changed the natural language processing paradigm towards a unified foundation model across domains and applications. |
| Approach: | They evaluate the performance of GPT-4 on a variety of radiology tasks . they find it outperforms or matches current SOTA radiology models . |
| Outcome: | The proposed model outperforms or matches current SOTA radiology models on a range of tasks. |