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Bias in reinforcement learning: A review in healthcare applications
Reinforcement learning (RL) can assist in medical decision making using patient data
collected in electronic health record (EHR) systems. RL, a type of machine learning, can use …
collected in electronic health record (EHR) systems. RL, a type of machine learning, can use …
Combining structured and unstructured data for predictive models: a deep learning approach
Background The broad adoption of electronic health records (EHRs) provides great
opportunities to conduct health care research and solve various clinical problems in …
opportunities to conduct health care research and solve various clinical problems in …
Guidance on the assurance of machine learning in autonomous systems (AMLAS)
R Hawkins, C Paterson, C Picardi, Y Jia… - ar** clinical prediction models. However, missing data are common in routinely …
A pragmatic ensemble strategy for missing values imputation in health records
Pristine and trustworthy data are required for efficient computer modelling for medical
decision-making, yet data in medical care is frequently missing. As a result, missing values …
decision-making, yet data in medical care is frequently missing. As a result, missing values …
[HTML][HTML] Explainable machine learning techniques to predict amiodarone-induced thyroid dysfunction risk: multicenter, retrospective study with external validation
YT Lu, HJ Chao, YC Chiang, HY Chen - Journal of Medical Internet …, 2023 - jmir.org
Background Machine learning offers new solutions for predicting life-threatening,
unpredictable amiodarone-induced thyroid dysfunction. Traditional regression approaches …
unpredictable amiodarone-induced thyroid dysfunction. Traditional regression approaches …