Primary Care

Latest AI and machine learning research in primary care for healthcare professionals.

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Identifying Cancer Patients at Risk for Heart Failure Using Machine Learning Methods.

Cardiotoxicity related to cancer therapies has become a serious issue, diminishing cancer treatment ...

HarborBot: A Chatbot for Social Needs Screening.

Accessing patients' social needs is a critical challenge at emergency departments (EDs). However, mo...

Evaluation of Combined Artificial Intelligence and Radiologist Assessment to Interpret Screening Mammograms.

IMPORTANCE: Mammography screening currently relies on subjective human interpretation. Artificial in...

Glucose outcomes of a learning-type artificial pancreas with an unannounced meal in type 1 diabetes.

BACKGROUND AND OBJECTIVES: Glycemic control with unannounced meals is the major challenge for artifi...

Automatic Lung Nodule Detection Combined With Gaze Information Improves Radiologists' Screening Performance.

Early diagnosis of lung cancer via computed tomography can significantly reduce the morbidity and mo...

A proposed health monitoring system using fuzzy inference system.

Due to the busy schedule of every human being in today's world, consciousness towards one's health h...

Automatic opportunistic osteoporosis screening using low-dose chest computed tomography scans obtained for lung cancer screening.

OBJECTIVE: Osteoporosis is a prevalent and treatable condition, but it remains underdiagnosed. In th...

Applying Machine Learning to Ultrafast Shape Recognition in Ligand-Based Virtual Screening.

Ultrafast Shape Recognition (USR), along with its derivatives, are Ligand-Based Virtual Screening (L...

Development of a system based on artificial intelligence to identify visual problems in children: study protocol of the TrackAI project.

INTRODUCTION: Around 70% to 80% of the 19 million visually disabled children in the world are due to...

Vitamin D insufficiency is associated with subclinical atherosclerosis in HIV-1-infected patients on combination antiretroviral therapy.

Vitamin D insufficiency has been associated with faster progression of atherosclerosis and increase...

Deep learning for screening of interstitial lung disease patterns in high-resolution CT images.

AIM: To develop a screening tool for the detection of interstitial lung disease (ILD) patterns using...

Hard exudate detection based on deep model learned information and multi-feature joint representation for diabetic retinopathy screening.

BACKGROUND AND OBJECTIVE: Diabetic retinopathy (DR), which is generally diagnosed by the presence of...

Efficient treatment of outliers and class imbalance for diabetes prediction.

Learning from outliers and imbalanced data remains one of the major difficulties for machine learnin...

The Prediction of Human Abdominal Adiposity Based on the Combination of a Particle Swarm Algorithm and Support Vector Machine.

: Abdominal adiposity is an important risk factor of chronic cardiovascular diseases, thus the predi...

An Artificial Neural Network-based Predictive Model to Support Optimization of Inpatient Glycemic Control.

Achieving glycemic control in critical care patients is of paramount importance, and has been linke...

Predicting 10-Year Risk of End-Organ Complications of Type 2 Diabetes With and Without Metabolic Surgery: A Machine Learning Approach.

OBJECTIVE: To construct and internally validate prediction models to estimate the risk of long-term ...

DeepCPI: A Deep Learning-based Framework for Large-scale in silico Drug Screening.

Accurate identification of compound-protein interactions (CPIs) in silico may deepen our understandi...

The application of artificial intelligence (AI) techniques to identify frailty within a residential aged care administrative data set.

INTRODUCTION: Research has shown that frailty, a geriatric syndrome associated with an increased ris...

Untargeted Metabolomics for Metabolic Diagnostic Screening with Automated Data Interpretation Using a Knowledge-Based Algorithm.

Untargeted metabolomics may become a standard approach to address diagnostic requests, but, at prese...

Policy Implications of Artificial Intelligence and Machine Learning in Diabetes Management.

PURPOSE OF REVIEW: Machine learning (ML) is increasingly being studied for the screening, diagnosis,...

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