Primary Care

Robot-assisted versus laparoscopic approach to concurrent bariatric surgery and hiatal hernia repair: propensity score matching analysis using the 2015-2018 MBSAQIP.

BACKGROUND: Up to 37% of class three obesity patients have a Hiatal Hernia (HH). Most of the existent HHs get repaired at the time of bariatric surgery. Although the robotic platform might offer potential technical advantages over traditional laparoscopy, the clinical outcomes of the concurrent bariatric surgery and HH repair comparing robotic vs laparoscopic approaches have not been reported.

Machine learning algorithms as new screening approach for patients with endometriosis.

Endometriosis-a systemic and chronic condition occurring in women of childbearing age-is a highly enigmatic disease with unresolved questions. While multiple biomarkers, genomic analysis, questionnaires, and imaging techniques have been advocated as screening and triage tests for endometriosis to replace diagnostic laparoscopy, none have been implemented routinely in clinical practice. We investig...

Cardiovascular disease detection using machine learning and carotid/femoral arterial imaging frameworks in rheumatoid arthritis patients.

The study proposes a novel machine learning (ML) paradigm for cardiovascular disease (CVD) detection in individuals at medium to high cardiovascular r...

A Novel Diabetes Healthcare Disease Prediction Framework Using Machine Learning Techniques.

Diabetes is a chronic disease that continues to be a significant and global concern since it affects the entire population's health. It is a metabolic...

Machine learning for emerging infectious disease field responses.

Emerging infectious diseases (EIDs), including the latest COVID-19 pandemic, have emerged and raised global public health crises in recent decades. Wi...

Smart Heart Disease Prediction System with IoT and Fog Computing Sectors Enabled by Cascaded Deep Learning Model.

Chronic illnesses like chronic respiratory disease, cancer, heart disease, and diabetes are threats to humans around the world. Among them, heart dise...

Artificial intelligence approaches to the determinants of women's vaginal dryness using general hospital data.

The aim of this study is to analyse the determinants of women's vaginal dryness using machine learning. Data came from Korea University Anam Hospital ...

Enabling Research and Clinical Use of Patient-Generated Health Data (the mindLAMP Platform): Digital Phenotyping Study.

BACKGROUND: There is a growing need for the integration of patient-generated health data (PGHD) into research and clinical care to enable personalized...

Panoramic tongue imaging and deep convolutional machine learning model for diabetes diagnosis in humans.

Diabetes is a serious metabolic disorder with high rate of prevalence worldwide; the disease has the characteristics of improper secretion of insulin ...

An Efficient Deep Learning Approach to Automatic Glaucoma Detection Using Optic Disc and Optic Cup Localization.

Glaucoma is an eye disease initiated due to excessive intraocular pressure inside it and caused complete sightlessness at its progressed stage. Wherea...

Point-of-care screening for heart failure with reduced ejection fraction using artificial intelligence during ECG-enabled stethoscope examination in London, UK: a prospective, observational, multicentre study.

BACKGROUND: Most patients who have heart failure with a reduced ejection fraction, when left ventricular ejection fraction (LVEF) is 40% or lower, are...

Deep learning-based pancreas volume assessment in individuals with type 1 diabetes.

Pancreas volume is reduced in individuals with diabetes and in autoantibody positive individuals at high risk for developing type 1 diabetes (T1D). St...

Research on User Experience of Sports Smart Bracelet Based on Fuzzy Comprehensive Appraisal and SSA-BP Neural Network.

Due to the marked increase in the prevalence of overweight and obesity worldwide and an environment leading to a series of chronic diseases, physical ...

TrendProbe: Time profile analysis of emerging contaminants by LC-HRMS non-target screening and deep learning convolutional neural network.

Peak prioritization is one of the key steps in non-target screening of environmental samples to direct the identification efforts to relevant and impo...

Rhabdomyolysis: An evidence-based approach.

A 76-year-old lady was found on the floor following a fall at home. She was uninjured, but unable to get up, and had been lying on the floor for rough...

Data Homogeneity Effect in Deep Learning-Based Prediction of Type 1 Diabetic Retinopathy.

This study is aimed at evaluating a deep transfer learning-based model for identifying diabetic retinopathy (DR) that was trained using a dataset with...

Prediction of coronary heart disease based on combined reinforcement multitask progressive time-series networks.

Coronary heart disease is the first killer of human health. At present, the most widely used approach of coronary heart disease diagnosis is coronary ...

Risk Assessment and Determination of Factors That Cause the Development of Hyperinsulinemia in School-Age Adolescents.

: Hyperinsulinemia and insulin resistance are not synonymous; if the risk of developing insulin resistance in adolescents is monitored, they do not ne...

Deep Learning in the Classification of Stage of Liver Fibrosis in Chronic Hepatitis B with Magnetic Resonance ADC Images.

Liver fibrosis in chronic hepatitis B is the pathological repair response of the liver to chronic injury, which is a key step in the development of va...

Multi-step ahead predictive model for blood glucose concentrations of type-1 diabetic patients.

Continuous monitoring of blood glucose (BG) levels is a key aspect of diabetes management. Patients with Type-1 diabetes (T1D) require an effective to...