5 papers
Patient-Centered Summarization Framework for AI Clinical Summarization: A Mixed-Methods Design
Maria Lizarazo Jimenez, Ana Gabriela Claros, Kieran Green +15
Large Language Models (LLMs) are increasingly demonstrating the potential to reach human-level performance in generating clinical summaries from patient-clinician conversations. Ho…
Artificial Intelligence-Enabled Analysis of Radiology Reports: Epidemiology and Consequences of Incidental Thyroid Findings
Felipe Larios, Mariana Borras-Osorio, Yuqi Wu +18
Importance Incidental thyroid findings (ITFs) are increasingly detected on imaging performed for non-thyroid indications. Their prevalence, features, and clinical consequences rema…
Longitudinal and Multimodal Recording System to Capture Real-World Patient-Clinician Conversations for AI and Encounter Research: Protocol
Misk Al Zahidy, Kerly Guevara Maldonado, Luis Vilatuna Andrango +7
The promise of AI in medicine depends on learning from data that reflect what matters to patients and clinicians. Most existing models are trained on electronic health records (EHR…
Developing an AI framework to automatically detect shared decision-making in patient-doctor conversations
Oscar J. Ponce-Ponte, David Toro-Tobon, Luis F. Figueroa +5
Shared decision-making (SDM) is necessary to achieve patient-centred care. Currently no methodology exists to automatically measure SDM at scale. This study aimed to develop an aut…
Use of natural language processing to extract and classify papillary thyroid cancer features from surgical pathology reports
Ricardo Loor-Torres, Yuqi Wu, Esteban Cabezas +10
Background We aim to use Natural Language Processing (NLP) to automate the extraction and classification of thyroid cancer risk factors from pathology reports. Methods We analyzed…