AIMC Topic: Machine Learning

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An East Coast Perspective on Artificial Intelligence and Machine Learning: Part 2: Ischemic Stroke Imaging and Triage.

Neuroimaging clinics of North America
Acute ischemic stroke constitutes approximately 85% of strokes. Most strokes occur in community settings; thus, automatic algorithms techniques are attractive for managing these cases. This article reviews the use of deep learning convolutional neura...

Machine Learning Algorithm Validation: From Essentials to Advanced Applications and Implications for Regulatory Certification and Deployment.

Neuroimaging clinics of North America
The deployment of machine learning (ML) models in the health care domain can increase the speed and accuracy of diagnosis and improve treatment planning and patient care. Translating academic research to applications that are deployable in clinical s...

VR and machine learning: novel pathways in surgical hands-on training.

Current opinion in urology
PURPOSE OF REVIEW: Surgical training has dramatically changed over the last decade. It has become not only the way to prepare surgeons for their everyday work, but also a way to certify their skills thus increasing patient safety. This article review...

A machine learning-based clinical decision support system to identify prescriptions with a high risk of medication error.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: To improve patient safety and clinical outcomes by reducing the risk of prescribing errors, we tested the accuracy of a hybrid clinical decision support system in prioritizing prescription checks.

Validation of a Machine Learning Algorithm to Predict 180-Day Mortality for Outpatients With Cancer.

JAMA oncology
IMPORTANCE: Machine learning (ML) algorithms can identify patients with cancer at risk of short-term mortality to inform treatment and advance care planning. However, no ML mortality risk prediction algorithm has been prospectively validated in oncol...

Artificial intelligence in the diagnosis, treatment and prevention of urinary stones.

Current opinion in urology
PURPOSE OF REVIEW: There has a been rapid progress in the use of artificial intelligence in all aspects of healthcare, and in urology, this is particularly astute in the overall management of urolithiasis. This article reviews advances in the use of ...

A systematic literature review of automatic Alzheimer's disease detection from speech and language.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: In recent years numerous studies have achieved promising results in Alzheimer's Disease (AD) detection using automatic language processing. We systematically review these articles to understand the effectiveness of this approach, identify ...

Patient Coded Severity and Payment Penalties Under the Hospital Readmissions Reduction Program: A Machine Learning Approach.

Medical care
OBJECTIVE: The objective of this study was to examine variation in hospital responses to the Centers for Medicare and Medicaid's expansion of allowable secondary diagnoses in January 2011 and its association with financial penalties under the Hospita...

Machine learning in the optimization of robotics in the operative field.

Current opinion in urology
PURPOSE OF REVIEW: The increasing use of robotics in urologic surgery facilitates collection of 'big data'. Machine learning enables computers to infer patterns from large datasets. This review aims to highlight recent findings and applications of ma...