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Solutions
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Solutions
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Whitepapers
Segmented Harmonic Loss: Handling Class-Imbalanced Multi-Label Clinical Data for Medical Coding with LLMs
October 10, 2023
CloudMedx dropout algorithm prioritizes patients and their transplant needs –Published by USCF
January 14, 2022
CloudMedx NLP algorithm 96.3% accurate for unstructured data extractions –Published by USCF
June 30, 2020
CloudMedx’s predicts survival for ALS with 82% accuracy – Published by Barrow Neurological Institute
April 14, 2020
CloudMedx algorithm predicts outcome scores in 11 days following TJA surgery –Published by USCF
March 6, 2020
CloudMedx is 80% accurate in predicting waitlist dropout for Hepatocellular Carcinoma patients –Published by UCSF
October 1, 2019
More Whitepapers on Google Scholar about CloudMedx AI
September 30, 2019