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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9453051 | PMC |
| http://dx.doi.org/10.1016/j.ihj.2022.07.004 | DOI Listing |
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Conjunctival Bulbar Redness Extraction Pipeline for High-Resolution Ocular Surface Photography.
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Institute of the Electrical and Biomedical Engineering, UMIT TIROL - Private University for Health Sciences and Health Technology, Hall in Tyrol, Austria.
Purpose: To extract conjunctival bulbar redness from standardized high-resolution ocular surface photographs of a novel imaging system by implementing an image analysis pipeline.
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A Symbolic AI Approach to Medical Training.
J Med Syst
January 2025
Computer Science Institute, DISIT, University of Eastern Piedmont, Alessandria, Italy.
In traditional medical education, learners are mostly trained to diagnose and treat patients through supervised practice. Artificial Intelligence and simulation techniques can complement such an educational practice. In this paper, we present GLARE-Edu, an innovative system in which AI knowledge-based methodologies and simulation are exploited to train learners "how to act" on patients based on the evidence-based best practices provided by clinical practice guidelines.
View Article and Find Full Text PDFMultimodal deep learning for predicting in-hospital mortality in heart failure patients using longitudinal chest X-rays and electronic health records.
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Shanxi Cardiovascular Hospital, 18 Yifen Street, Taiyuan, 030024, Shanxi, China.
Amid an aging global population, heart failure has become a leading cause of hospitalization among older people. Its high prevalence and mortality rates underscore the importance of accurate mortality prediction for swift disease progression assessment and better patient outcomes. The evolution of artificial intelligence (AI) presents new avenues for predicting heart failure mortality.
View Article and Find Full Text PDFA dataset and benchmark for hospital course summarization with adapted large language models.
J Am Med Inform Assoc
December 2024
Department of Radiology, Stanford University, Stanford, CA 94304, United States.
Objective: Brief hospital course (BHC) summaries are clinical documents that summarize a patient's hospital stay. While large language models (LLMs) depict remarkable capabilities in automating real-world tasks, their capabilities for healthcare applications such as synthesizing BHCs from clinical notes have not been shown. We introduce a novel preprocessed dataset, the MIMIC-IV-BHC, encapsulating clinical note and BHC pairs to adapt LLMs for BHC synthesis.
View Article and Find Full Text PDFRisk prediction for elderly cognitive impairment by radiomic and morphological quantification analysis based on a cerebral MRA imaging cohort.
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Institute of PLA Geriatric Medicine, The Second Medical Center & National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China.
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