Primary Care

Assistive AI in Lung Cancer Screening: A Retrospective Multinational Study in the United States and Japan.

Purpose To evaluate the impact of an artificial intelligence (AI) assistant for lung cancer screenin...

Screening Automation in Systematic Reviews: Analysis of Tools and Their Machine Learning Capabilities.

Systematic reviews provide robust evidence but require significant human labor, a challenge that can...

Trends in the Prevalence of Common Retinal and Optic Nerve Diseases in China: An Artificial Intelligence Based National Screening.

PURPOSE: Retinal and optic nerve diseases have become the primary cause of irreversible vision loss ...

B-mode US and Deep Learning Rivals Shear-Wave Elastography in Screening for Fibrosis.

Deep learning to assess right ventricular ejection fraction from two-dimensional echocardiograms in precapillary pulmonary hypertension.

BACKGROUND: Precapillary pulmonary hypertension (PH) is characterized by a sustained increase in rig...

Artificial intelligence in lung cancer screening: Detection, classification, prediction, and prognosis.

BACKGROUND: The exceptional capabilities of artificial intelligence (AI) in extracting image informa...

Artificial intelligence-driven cardiac amyloidosis screening.

Deep Learning-Augmented ECG Analysis for Screening and Genotype Prediction of Congenital Long QT Syndrome.

IMPORTANCE: Congenital long QT syndrome (LQTS) is associated with syncope, ventricular arrhythmias, ...

[Screening for Characteristic Genes of Different Traditional Chinese Medicine Syndromes of Psoriasis Vulgaris: A Study Based on Bioinformatics and Machine Learning].

OBJECTIVE: To screen for the key characteristic genes of the psoriasis vulgaris (PV) patients with d...

Use of artificial intelligence and radio genomics in neuroradiology and the future of brain tumour imaging and surgical planning in low- and middleincome countries.

Brain tumour diagnosis involves assessing various radiological and histopathological parameters. Ima...

AI for Detection of Tuberculosis: Implications for Global Health.

Tuberculosis, which primarily affects developing countries, remains a significant global health conc...

Screening of key immunerelated gene in Parkinsons disease based on WGCNA and machine learning.

OBJECTIVES: Abnormal immune system activation and inflammation are crucial in causing Parkinson's di...

[Predicting the risk of becoming eligible for the disability pension: Machine learning methods applied to French health data].

INTRODUCTION: Benefiting from the disability pension implies morbid (physical and psychological) and...

Battle of the minds: AI vs mental health professionals in mental wellness care.

A Framework for Implementing Disease Prevention and Behavior Change Evidence at Scale.

The current corpus of evidence-based information for chronic disease prevention and treatment is vas...

Automatically pre-screening patients for the rare disease aromatic l-amino acid decarboxylase deficiency using knowledge engineering, natural language processing, and machine learning on a large EHR population.

OBJECTIVES: Electronic health record (EHR) data may facilitate the identification of rare diseases i...

Deep learning-based BMI inference from structural brain MRI reflects brain alterations following lifestyle intervention.

Obesity is associated with negative effects on the brain. We exploit Artificial Intelligence (AI) to...

Letter to the editor on "Automated classification of fat-infiltrated axillary lymph nodes on screening mammograms".

Geriatric depression and anxiety screening via deep learning using activity tracking and sleep data.

BACKGROUND: Geriatric depression and anxiety have been identified as mood disorders commonly associa...

StructuralDPPIV: a novel deep learning model based on atom structure for predicting dipeptidyl peptidase-IV inhibitory peptides.

MOTIVATION: Diabetes is a chronic metabolic disorder that has been a major cause of blindness, kidne...

Development of a pharmaceutical science systematic review process using a semi-automated machine learning tool: Intravenous drug compatibility in the neonatal intensive care setting.

Our objective was to establish and test a machine learning-based screening process that would be app...