Health Policy

External Validation of a Deep Learning Model for Predicting Mammographic Breast Density in Routine Clinical Practice.

RATIONALE AND OBJECTIVES: Federal legislation requires patient notification of dense mammographic br...

Separation of HCM and LQT Cardiac Diseases with Machine Learning of Ca2+ Transient Profiles.

BACKGROUND:  Modeling human cardiac diseases with induced pluripotent stem cells not only enables to...

Hybrid decision tree-based machine learning models for short-term water quality prediction.

Water resources are the foundation of people's life and economic development, and are closely relate...

Predicting Forage Quality of Warm-Season Legumes by Near Infrared Spectroscopy Coupled with Machine Learning Techniques.

Warm-season legumes have been receiving increased attention as forage resources in the southern Unit...

Artificial intelligence: Who is responsible for the diagnosis?

The aim of the paper is to find an answer to the question "Who or what is responsible for the benefi...

The influence of image quality on diagnostic performance of a machine learning-based fractional flow reserve derived from coronary CT angiography.

OBJECTIVE: To investigate the effect of image quality of coronary CT angiography (CCTA) on the diagn...

Factors Influencing Delivery of Cancer Survivorship Care Plans: A National Patterns of Care Study.

Nearly half of all Americans will develop cancer at least once in their lifetime. Through improved s...

Domain-invariant interpretable fundus image quality assessment.

Objective and quantitative assessment of fundus image quality is essential for the diagnosis of reti...

Does robot-assisted gait training improve mobility, activities of daily living and quality of life in stroke? A single-blinded, randomized controlled trial.

The purpose of this study was to investigate the effects of robot-assisted gait training (RAGT) on m...

Cancer Prevention Using Machine Learning, Nudge Theory and Social Impact Bond.

There have been prior attempts to utilize machine learning to address issues in the medical field, p...

Predicting the Associations between Meridians and Chinese Traditional Medicine Using a Cost-Sensitive Graph Convolutional Neural Network.

Natural products are the most important and commonly used in Traditional Chinese Medicine (TCM) for ...

Economic Evaluation of Robot-Based Telemedicine Consultation Services.

Through information and communication technology, telemedicine can deliver medical care without tim...

Investigating the use of data-driven artificial intelligence in computerised decision support systems for health and social care: A systematic review.

There is growing interest in the potential of artificial intelligence to support decision-making in ...

Image Quality and Lesion Detection on Deep Learning Reconstruction and Iterative Reconstruction of Submillisievert Chest and Abdominal CT.

The objective of this study was to compare image quality and clinically significant lesion detectio...

First-in-human evaluation of a hand-held automated venipuncture device for rapid venous blood draws.

Obtaining venous access for blood sampling or intravenous (IV) fluid delivery is an essential first ...

Low-Cost Robotic Guide Based on a Motor Imagery Brain-Computer Interface for Arm Assisted Rehabilitation.

Motor imagery has been suggested as an efficient alternative to improve the rehabilitation process o...

Regional anaesthesia and quality of recovery after surgery.

Use of Artificial Intelligence-Based Analytics From Live Colonoscopies to Optimize the Quality of the Colonoscopy Examination in Real Time: Proof of Concept.

Validation of deep-learning image reconstruction for coronary computed tomography angiography: Impact on noise, image quality and diagnostic accuracy.

BACKGROUND: Advances in image reconstruction are necessary to decrease radiation exposure from coron...

Cost-effectiveness of targeted screening for the identification of patients with atrial fibrillation: evaluation of a machine learning risk prediction algorithm.

As many cases of atrial fibrillation (AF) are asymptomatic, patients often remain undiagnosed until...

A two-step automated quality assessment for liver MR images based on convolutional neural network.

PURPOSE: To propose an automatic approach based on a convolutional neural network (CNN) to evaluate ...