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TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods

TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods
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Northern Cape , South Africa , United States , United Kingdom , University College , New South Wales , Dan Adler , Richiardi Jonas , Victor Castro , Stacey Fisher , Boris Janssen , Laure Wynants , Vinyas Harish , Daniel Stahl , Viknesh Sounderajah , Evangelos Kanoulas , Conrad Harrison , Alex Garaiman , Junfeng Wang , Brooke Levis , Frank Rademakers , Adrian Barnett , Van Leeuwen , Jie Ma , Zane Perkins , Rachel Kuo ,

Development and Validation of a Risk Score Predicting Death Without Transplant in Adult Heart Transplant Candidates | Surgery | JAMA

This study develops and validates a multivariable prediction model to rank order adult heart transplant candidates by medical urgency. ....

National Institutes Of Health , United States , Williamf Parker , University Of Chicago , Blood Institute , R Foundation For Statistical Computing , Us Department Of Health , Transplantation Network , Security Administration , National Institute , University Of Chicago Biological Sciences Division , Greenwall Foundation , National Institute Of Diabetes , Department Of Defense , Boehringer Ingelheim , National Heart , Human Services , Candidate Risk Score , French Candidate Risk Score , Organ Procurement , Risk Score , Study Population , Scientific Registry , Transplant Recipients , Transparent Reporting , Multivariable Prediction Model ,

Evaluation of clinical prediction models (part 3): calculating the sample size required for an external validation study

An external validation study evaluates the performance of a prediction model in new data, but many of these studies are too small to provide reliable answers. In the third article of their series on model evaluation, Riley and colleagues describe how to calculate the sample size required for external validation studies, and propose to avoid rules of thumb by tailoring calculations to the model and setting at hand.

External validation studies evaluate the performance of one or more prediction models (eg, developed previously using statistical, machine learning, or artificial intelligence approaches) in a different dataset to that used in the model development process.1 2 3 Part 2 in our series describes how to undertake a high quality external validation study,4 including the need to estimate model performance measures such as calibration (agreement between observed and predicted values), discrimination (separation between predicted values in those with and without an outcome eve ....

United Kingdom , City Of , Garys Collins , Lucinda Archer , Kym Ie Snell , Ben Van Calster , Thomas Pa Debray , Van Calster , Richardd Riley , Maarten Van Smeden , Care Research , Cancer Research United Kingdom , Research Foundation Flanders , Birmingham Biomedical Research Centre , Better Methods Research , Sciences Research Council , University Of Birmingham , University Hospitals Birmingham , Department Of Health , Research Council , National Institute For Health , Transparent Reporting , Individual Prognosis , Physical Sciences Research Council , Medical Research Council , National Institute ,

Development and Validation of the COVID-19 Hospitalized Patient Deterioration Index

The authors developed and validated an accurate, well-calibrated, easy-to-implement COVID-19 hospitalized patient deterioration index to identify patients at high or low risk of clinical deterioration. ....

United States , New York , South Lake , Baldwin Park , Los Angeles , University Of Washington , S Los Robles , Van Calster , China Medical Treatment Expert Group For Covid , Nw Collaborative Organisation For Respiratory Research , Department Of Health Systems Science , Los Angeles Medical Center , Southern California Permanente Medical Group , Baldwin Park Medical Center , Uw Medicine At South Lake Union , Cohort Assembly , Department Of Biomedical Informatics , Us Census Bureau , Department Of Research , National Heart , Patient Deterioration Index , Epic Deterioration Index , Kaiser Permanente Southern California , Transparent Reporting , Multivariable Prediction Model , Individual Prognosis ,

How Radiologists Can Expand the Utilization of AI

AI is reshaping healthcare practice through innovative tools and technologies that augment the capabilities of healthcare providers while streamlining workflows and enhancing diagnostic accuracy ....

United States , John Mccarthy , Meeru Kumar , Akshay Chaand , Drug Administration , Texasam School Of Dentistry , Kurukshetra University , Radiological Society Of North America , Radiological Society , North America , Radiomics Quality Score , Individual Prognosis , Oral Medicine , Maxillofacial Radiology ,