Primary Care

Identification of Diabetes Risk Factors in Chronic Cardiovascular Patients.

Specific predictive models for diabetes polyneuropathy based on screening methods, for example Nerve...

Rosiglitazone-induced changes in the oxidative stress metabolism and fatty acid composition in relation with trace element status in the primary adipocytes.

BACKGROUND: Metabolic syndrome, obesity and type 2 diabetes are metabolic disorders characterized by...

Assessment and prediction of restless leg syndrome (RLS) in patients with diabetes mellitus type II through artificial intelligence (AI).

This study aimed to diagnose the incidence of restless leg syndrome (RLS) in patients with diabetes ...

Effect of artificial intelligence-based triaging of breast cancer screening mammograms on cancer detection and radiologist workload: a retrospective simulation study.

BACKGROUND: We examined the potential change in cancer detection when using an artificial intelligen...

Artificial intelligence for diabetic retinopathy screening, prediction and management.

PURPOSE OF REVIEW: Diabetic retinopathy is the most common specific complication of diabetes mellitu...

Gut Microbiota in T1DM-Onset Pediatric Patients: Machine-Learning Algorithms to Classify Microorganisms as Disease Linked.

AIMS: The purpose of this work is to find the gut microbial fingerprinting of pediatric patients wit...

[Artificial intelligence for cancer detection in breast cancer screening].

Artificial intelligence (AI) has the potential to increase quality and efficiency of breast cancer s...

[Rapid screening and determination of fentanyl and its analogues in drugs by liquid chromatography- quadrupole time-of-flight mass spectrometry].

A method based on liquid chromatography coupled with high-resolution quadrupole time-of-flight mass ...

Accurate Screening of COVID-19 Using Attention-Based Deep 3D Multiple Instance Learning.

Automated Screening of COVID-19 from chest CT is of emergency and importance during the outbreak of ...

Prior-Attention Residual Learning for More Discriminative COVID-19 Screening in CT Images.

We propose a conceptually simple framework for fast COVID-19 screening in 3D chest CT images. The fr...

Artificial Intelligence for Personalized Preventive Adolescent Healthcare.

Recent advances in artificial intelligence (AI) are creating new opportunities for personalizing tec...

Workforce Shortage for Retinopathy of Prematurity Care and Emerging Role of Telehealth and Artificial Intelligence.

Retinopathy of prematurity (ROP) is the leading cause of childhood blindness in very-low-birthweight...

Assessing the Accuracy of a Deep Learning Method to Risk Stratify Indeterminate Pulmonary Nodules.

The management of indeterminate pulmonary nodules (IPNs) remains challenging, resulting in invasive...

Data Mining and Fusion of Unobtrusive Sensing Solutions for Indoor Activity Recognition.

This paper proposes the fusion of data from unobtrusive sensing solutions for the recognition and cl...

An Empirical Method of Automatic Pattern Extraction for Clinical Text Classification.

Clinical text classification is an indispensable and extensively studied problem in medical text pro...

Learning Decision Ensemble using a Graph Neural Network for Comorbidity Aware Chest Radiograph Screening.

Chest radiographs are primarily employed for the screening of cardio, thoracic and pulmonary conditi...

A Systematic Search over Deep Convolutional Neural Network Architectures for Screening Chest Radiographs.

Chest radiographs are primarily employed for the screening of pulmonary and cardio-/thoracic conditi...

Predicting complications of diabetes mellitus using advanced machine learning algorithms.

OBJECTIVE: We sought to predict if patients with type 2 diabetes mellitus (DM2) would develop 10 sel...

Predictive Modeling of Pressure Injury Risk in Patients Admitted to an Intensive Care Unit.

BACKGROUND: Pressure injuries are an important problem in hospital care. Detecting the population at...

Commentary: How useful is a deep learning smartphone application for screening for amblyogenic risk factors?

Application of deep learning and image processing analysis of photographs for amblyopia screening.

PURPOSE: Photo screeners and autorefractors have been used to screen children for amblyopia risk fac...