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Clinical Decision-Making

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Emergency department disposition prediction using a deep neural network with integrated clinical narratives and structured data.

International journal of medical informatics
BACKGROUND: Emergency department (ED) overcrowding has been a serious issue and demands effective clinical decision-making of patient disposition. In previous studies, emergency clinical narratives provide a rich context for clinical decisions. We ai...

Opening the black box of artificial intelligence for clinical decision support: A study predicting stroke outcome.

PloS one
State-of-the-art machine learning (ML) artificial intelligence methods are increasingly leveraged in clinical predictive modeling to provide clinical decision support systems to physicians. Modern ML approaches such as artificial neural networks (ANN...

Machine Learning Methods for Precision Medicine Research Designed to Reduce Health Disparities: A Structured Tutorial.

Ethnicity & disease
Precision medicine research designed to reduce health disparities often involves studying multi-level datasets to understand how diseases manifest disproportionately in one group over another, and how scarce health care resources can be directed prec...

Artificial intelligence in medicine.

Early human development
Artificial Intelligence (AI) is based on accurate decision-making processes which can be carried out independently by a machine. AI may be subdivided into strong AI (with consciousness and intentionality) and weak AI (lacking both and programmed to p...

Improved Prediction of Surgical Resectability in Patients with Glioblastoma using an Artificial Neural Network.

Scientific reports
In managing a patient with glioblastoma (GBM), a surgeon must carefully consider whether sufficient tumour can be removed so that the patient can enjoy the benefits of decompression and cytoreduction, without impacting on the patient's neurological s...

Interpretable Artificial Intelligence: Why and When.

AJR. American journal of roentgenology
The purpose of this article is to discuss the problem of interpretability of artificial intelligence (AI) and highlight the need for continuing scientific discovery using AI algorithms to deal with medical big data. A plethora of AI algorithms are ...

The applications of machine learning in plastic and reconstructive surgery: protocol of a systematic review.

Systematic reviews
BACKGROUND: Machine learning, a subset of artificial intelligence, is a set of models and methods that can automatically detect patterns in vast amounts of data, extract information and use it to perform various kinds of decision-making under uncerta...

Artificial intelligence in abdominal aortic aneurysm.

Journal of vascular surgery
OBJECTIVE: Abdominal aortic aneurysm (AAA) is a life-threatening disease, and the only curative treatment relies on open or endovascular repair. The decision to treat relies on the evaluation of the risk of AAA growth and rupture, which can be diffic...

Learning from Artificial Intelligence and Big Data in Health Care.

European journal of vascular and endovascular surgery : the official journal of the European Society for Vascular Surgery