Primary Care

Identifying Young Adults at High Risk for Weight Gain Using Machine Learning.

INTRODUCTION: Weight gain among young adults continues to increase. Identifying adults at high risk for weight gain and intervening before they gain weight could have a major public health impact. Our objective was to develop and test electronic health record-based machine learning models to predict weight gain in young adults with overweight/class 1 obesity.

Pediatric Single-Incision Robotic Cholecystectomy: A 6-Year Update from a Single Institution.

In children, gallbladder disease has become more common due to the rise in childhood obesity and subsequent shift in etiology. While the gold standard of surgical management remains a laparoscopic technique, there has been increasing interest in robotic-assisted techniques. The aim of this study is to report a 6-year update on the experience of treating gallbladder disease with robotic-assisted s...

Discovery of senolytics using machine learning.

Cellular senescence is a stress response involved in ageing and diverse disease processes including cancer, type-2 diabetes, osteoarthritis and viral ...

Deep learning-based classification model for GPR151 activator activity prediction.

BACKGROUND: GPR151 is a kind of protein belonging to G protein-coupled receptor family that is closely associated with a variety of physiological and ...

CoAt-Mixer: Self-attention deep learning framework for left ventricular hypertrophy using electrocardiography.

Left ventricular hypertrophy is a significant independent risk factor for all-cause mortality and morbidity, and an accurate diagnosis at an early sta...

Brain tumor detection and screening using artificial intelligence techniques: Current trends and future perspectives.

A brain tumor is an abnormal mass of tissue located inside the skull. In addition to putting pressure on the healthy parts of the brain, it can lead t...

Predicting blood pressure from face videos using face diagnosis theory and deep neural networks technique.

Hypertension is a major cause of cardiovascular diseases. Accurate and convenient measurement of blood pressure are necessary for the detection, treat...

A diabetes prediction model based on Boruta feature selection and ensemble learning.

BACKGROUND AND OBJECTIVE: As a common chronic disease, diabetes is called the "second killer" among modern diseases. Currently, there is no medical cu...

Robot-assisted partial nephrectomy in morbidly obese patients: a VCQI database study.

To compare perioperative outcomes following robot-assisted partial nephrectomy (RAPN) in patients with morbid obesity (body mass index (BMI > 40 kg/m)...

An Assessment of How Clinicians and Staff Members Use a Diabetes Artificial Intelligence Prediction Tool: Mixed Methods Study.

BACKGROUND: Nearly one-third of patients with diabetes are poorly controlled (hemoglobin A≥9%). Identifying at-risk individuals and providing them wit...

Screening outcome for interpretation by the first and second reader in a population-based mammographic screening program with independent double reading.

BACKGROUND: Double reading of screening mammograms is associated with a higher rate of screen-detected cancer than single reading, but different strat...

Machine Learning-Based Time in Patterns for Blood Glucose Fluctuation Pattern Recognition in Type 1 Diabetes Management: Development and Validation Study.

BACKGROUND: Continuous glucose monitoring (CGM) for diabetes combines noninvasive glucose biosensors, continuous monitoring, cloud computing, and anal...

A real-world evaluation of the implementation of NLP technology in abstract screening of a systematic review.

The laborious and time-consuming nature of systematic review production hinders the dissemination of up-to-date evidence synthesis. Well-performing na...

Deep learning-based screening tool for rotator cuff tears on shoulder radiography.

BACKGROUND: Early diagnosis of rotator cuff tears is essential for appropriate and timely treatment. Although radiography is the most used technique i...

Deep Learning-Based Image Analysis of Liver Steatosis in Mouse Models.

The incidence of nonalcoholic fatty liver disease is a continuously growing health problem worldwide, along with obesity. Therefore, novel methods to ...

Opportunistic Screening: Scientific Expert Panel.

Radiologic tests often contain rich imaging data not relevant to the clinical indication. Opportunistic screening refers to the practice of systematic...

Standalone AI for Breast Cancer Detection at Screening Digital Mammography and Digital Breast Tomosynthesis: A Systematic Review and Meta-Analysis.

Background There is considerable interest in the potential use of artificial intelligence (AI) systems in mammographic screening. However, it is essen...

A deep learning method for continuous noninvasive blood pressure monitoring using photoplethysmography.

. The aim of this study is to investigate continuous blood pressure waveform estimation from a plethysmography (PPG) signal, thus providing more human...

Accurate deep learning model using semi-supervised learning and Noisy Student for cervical cancer screening in low magnification images.

Deep learning technology has been used in the medical field to produce devices for clinical practice. Deep learning methods in cytology offer the pote...

A family-centered orthodontic screening approach using a machine learning-based mobile application.

BACKGROUND/PURPOSE: Skeletal orthodontic deformities can have functional and aesthetic consequences, making early detection critical. This study aimed...