Primary Care

Predicting risk of overweight or obesity in Chinese preschool-aged children using artificial intelligence techniques.

OBJECTIVES: We adopted the machine-learning algorithms and deep-learning sequential model to determi...

Learning deep neural networks' architectures using differential evolution. Case study: Medical imaging processing.

The COVID-19 pandemic has changed the way we practice medicine. Cancer patient and obstetric care la...

Delta Machine Learning to Improve Scoring-Ranking-Screening Performances of Protein-Ligand Scoring Functions.

Protein-ligand scoring functions are widely used in structure-based drug design for fast evaluation ...

(De)troubling transparency: artificial intelligence (AI) for clinical applications.

Artificial intelligence (AI) and machine learning (ML) techniques occupy a prominent role in medical...

Sensor Screening Methodology for Virtually Sensing Transmission Input Loads of a Wind Turbine Using Machine Learning Techniques and Drivetrain Simulations.

The ongoing trend of building larger wind turbines (WT) to reach greater economies of scale is contr...

rECHOmmend: An ECG-Based Machine Learning Approach for Identifying Patients at Increased Risk of Undiagnosed Structural Heart Disease Detectable by Echocardiography.

BACKGROUND: Timely diagnosis of structural heart disease improves patient outcomes, yet many remain ...

Continuous-time probabilistic models for longitudinal electronic health records.

Analysis of longitudinal Electronic Health Record (EHR) data is an important goal for precision medi...

A Detailed Systematic Review on Retinal Image Segmentation Methods.

The separation of blood vessels in the retina is a major aspect in detecting ailment and is carried ...

Suicide Risk Prediction in Clinical Settings-Additional Considerations for Face-to-Face Screening and Machine Learning Approaches.

Using Occlusion-Based Saliency Maps to Explain an Artificial Intelligence Tool in Lung Cancer Screening: Agreement Between Radiologists, Labels, and Visual Prompts.

Occlusion-based saliency maps (OBSMs) are one of the approaches for interpreting decision-making pro...

Does imbalance in chest X-ray datasets produce biased deep learning approaches for COVID-19 screening?

BACKGROUND: The health crisis resulting from the global COVID-19 pandemic highlighted more than ever...

Comparison of radiologist versus natural language processing-based image annotations for deep learning system for tuberculosis screening on chest radiographs.

Although natural language processing (NLP) can rapidly extract disease labels from radiology reports...

Predicting Abnormal Amyloid Burden: Can Machine Learning Become a Future Tool in Preventive Neurology?

Very low-volume interval training improves nonalcoholic fatty liver disease fibrosis score and cardiometabolic health in adults with obesity and metabolic syndrome.

Non-alcoholic fatty liver disease (NAFLD) and cardiometabolic disorders are highly prevalent in obes...

Depression screening using a non-verbal self-association task: A machine-learning based pilot study.

BACKGROUND: Effective screening is important to combat the raising burden of depression and opens a ...

Machine learning prediction of gestational age from metabolic screening markers resistant to ambient temperature transportation: Facilitating use of this technology in low resource settings of South Asia and East Africa.

BACKGROUND: Knowledge of gestational age is critical for guiding preterm neonatal care. In the last ...

Deep neural networks learn general and clinically relevant representations of the ageing brain.

The discrepancy between chronological age and the apparent age of the brain based on neuroimaging da...

Joint optic disk and cup segmentation for glaucoma screening using a region-based deep learning network.

OBJECTIVES: To develop and validate an end-to-end region-based deep convolutional neural network (R-...

A Novel Approach for Feature Selection and Classification of Diabetes Mellitus: Machine Learning Methods.

An active research area where the experts from the medical field are trying to envisage the problem ...

Robot-enhanced diabetes care for middle-aged and older adults living with diabetes in the community: A small sample size mixed-method evaluation.

PURPOSE: This study assessed robot-enhanced healthcare in practical settings for the purpose of comm...

Cost-effectiveness of artificial intelligence for screening colonoscopy: a modelling study.

BACKGROUND: Artificial intelligence (AI) tools increase detection of precancerous polyps during colo...