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Clinical Decision-Making

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Dynamic multi-outcome prediction after injury: Applying adaptive machine learning for precision medicine in trauma.

PloS one
OBJECTIVE: Machine learning techniques have demonstrated superior discrimination compared to conventional statistical approaches in predicting trauma death. The objective of this study is to evaluate whether machine learning algorithms can be used to...

Incorporating causal factors into reinforcement learning for dynamic treatment regimes in HIV.

BMC medical informatics and decision making
BACKGROUND: Reinforcement learning (RL) provides a promising technique to solve complex sequential decision making problems in health care domains. However, existing studies simply apply naive RL algorithms in discovering optimal treatment strategies...

Inverse reinforcement learning for intelligent mechanical ventilation and sedative dosing in intensive care units.

BMC medical informatics and decision making
BACKGROUND: Reinforcement learning (RL) provides a promising technique to solve complex sequential decision making problems in health care domains. To ensure such applications, an explicit reward function encoding domain knowledge should be specified...

Automatic classification of ultrasound breast lesions using a deep convolutional neural network mimicking human decision-making.

European radiology
OBJECTIVES: To evaluate a deep convolutional neural network (dCNN) for detection, highlighting, and classification of ultrasound (US) breast lesions mimicking human decision-making according to the Breast Imaging Reporting and Data System (BI-RADS).

The day when computers read between lines.

Japanese journal of radiology
There is a growing notion that artificial general intelligence (AGI) will replace some of the work done by trained professionals, including physicians. This idea, however, seems to have logical leap; herein, we discuss three problems that are signifi...

The Role of a Decision Support System in Back Pain Diagnoses: A Pilot Study.

BioMed research international
It is the main goal of this study to investigate the concordance of a decision support system and the recommendation of spinal surgeons regarding back pain. 111 patients had to complete the decision support system. Furthermore, their illness was diag...

Review of Medical Decision Support and Machine-Learning Methods.

Veterinary pathology
Machine-learning methods can assist with the medical decision-making processes at the both the clinical and diagnostic levels. In this article, we first review historical milestones and specific applications of computer-based medical decision support...

An attention based deep learning model of clinical events in the intensive care unit.

PloS one
This study trained long short-term memory (LSTM) recurrent neural networks (RNNs) incorporating an attention mechanism to predict daily sepsis, myocardial infarction (MI), and vancomycin antibiotic administration over two week patient ICU courses in ...