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Development and assessment of a machine learning tool for predicting emergency admission in Scotland.
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Publisher Correction: Development and assessment of a machine learning tool for predicting emergency admission in Scotland.
Liley J. et al, (2024), NPJ digital medicine, 7
Assessing the Performance of Machine Learning Methods Trained on Public Health Observational Data: A Case Study From COVID-19.
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Characterising the genetic architecture of changes in adiposity during adulthood using electronic health records.
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Identification and validation of a machine learning model of complete response to radiation in rectal cancer reveals immune infiltrate and TGFβ as key predictors.
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A large-scale and PCR-referenced vocal audio dataset for COVID-19
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Equity in medical devices: trainers and educators play a vital role.
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To do no harm - and the most good - with AI in health care.
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Approximations to the Fisher Information Metric of Deep Generative Models for Out-Of-Distribution Detection
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Audio-based AI classifiers show no evidence of improved COVID-19 screening over simple symptoms checkers
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Age-dependent topic modeling of comorbidities in UK Biobank identifies disease subtypes with differential genetic risk
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Authors’ reply to the Discussion of ‘Martingale Posterior Distributions’
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Where Medical Statistics Meets Artificial Intelligence.
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Making the invisible visible: what can we do about biased AI in medical devices?
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Optimal strategies for learning multi-ancestry polygenic scores vary across traits
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Comparison of machine learning techniques in prediction of mortality following cardiac surgery: analysis of over 220 000 patients from a large national database.
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