Primary Care

An explainable machine learning-based clinical decision support system for prediction of gestational diabetes mellitus.

Gestational Diabetes Mellitus (GDM), a common pregnancy complication associated with many maternal a...

Independent External Validation of Artificial Intelligence Algorithms for Automated Interpretation of Screening Mammography: A Systematic Review.

PURPOSE: The aim of this study was to describe the current state of science regarding independent ex...

Application of ensemble machine learning algorithms on lifestyle factors and wearables for cardiovascular risk prediction.

This study looked at novel data sources for cardiovascular risk prediction including detailed lifest...

A full pipeline of diagnosis and prognosis the risk of chronic diseases using deep learning and Shapley values: The Ravansar county anthropometric cohort study.

Anthropometry is a Greek word that consists of the two words "Anthropo" meaning human species and "m...

Time to Scrutinize and Revise the Fine Print of Lung Cancer Screening Using Low-Dose CT: Seeking Greater Confidence in Cancer Detectability.

The Anti-Adiposity Mechanisms of Ampelopsin and Vine Tea Extract in High Fat Diet and Alcohol-Induced Fatty Liver Mouse Models.

(AG) is an ancient medicinal plant that is mainly distributed and used in southwest China. It exert...

Multimodal deep learning applied to classify healthy and disease states of human microbiome.

Metagenomic sequencing methods provide considerable genomic information regarding human microbiomes,...

Improving the In-Hospital Mortality Prediction of Diabetes ICU Patients Using a Process Mining/Deep Learning Architecture.

Diabetes intensive care unit (ICU) patients are at increased risk of complications leading to in-hos...

Detection of metallic objects on digital radiographs with convolutional neural networks: A MRI screening tool.

INTRODUCTION: Screening for metallic implants and foreign bodies before magnetic resonance imaging (...

Application of a Machine Learning Technology in the Definition of Metabolically Healthy and Unhealthy Status: A Retrospective Study of 2567 Subjects Suffering from Obesity with or without Metabolic Syndrome.

The key factors playing a role in the pathogenesis of metabolic alterations observed in many patient...

Automation of literature screening using machine learning in medical evidence synthesis: a diagnostic test accuracy systematic review protocol.

BACKGROUND: Systematic review is an indispensable tool for optimal evidence collection and evaluatio...

A deep learning model for screening type 2 diabetes from retinal photographs.

BACKGROUND AND AIMS: We aimed to develop and evaluate a non-invasive deep learning algorithm for scr...

Ligand Based Virtual Screening Using Self-organizing Maps.

Conventional drug discovery methods rely primarily on in-vitro experiments with a target molecule an...

Novel Model Based on Artificial Neural Networks to Predict Short-Term Temperature Evolution in Museum Environment.

The environmental microclimatic characteristics are often subject to fluctuations of considerable im...

Optimizing risk-based breast cancer screening policies with reinforcement learning.

Screening programs must balance the benefit of early detection with the cost of overscreening. Here,...

Automatic coronavirus disease 2019 diagnosis based on chest radiography and deep learning - Success story or dataset bias?

PURPOSE: Over the last 2 years, the artificial intelligence (AI) community has presented several aut...

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 en...

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...

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...

Machine learning for emerging infectious disease field responses.

Emerging infectious diseases (EIDs), including the latest COVID-19 pandemic, have emerged and raised...

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 ...