Preventive Care

Artificial intelligence-assisted reading of non-contrast prostate MRI: application and concordance with expert interpretation in a screening population within the PROSA trial.

OBJECTIVES: Non-contrast MRI (bi-parametric MRI-bpMRI) has been investigated as a potential tool to be integrated in clinically significant prostate cancer (csPCa) screening. Moreover, artificial intelligence (AI) is emerging too as a potential support, especially for less-experienced radiologists. Therefore, the aim of this study was to evaluate the effectiveness of an AI-based software in csPCa ...

Artificial Intelligence-Assisted Point-of-Care Ultrasound for Evaluating Left Ventricular Ejection Fraction: A Systematic Review of Prospective Observational Studies.

Artificial intelligence (AI) embedded in point-of-care ultrasound (POCUS) could reduce operator dependence in left ventricular ejection fraction (LVEF) assessment and accelerate bedside decision making by non-cardiologists and non-radiologists. Prospective comparative studies evaluating real-time AI-assisted POCUS for LVEF across point-of-care settings were systematically reviewed. The PubMed/MEDL...

Toward practical screening of mortality risk: Insights from interpretable machine learning in NHANES.

BACKGROUND: Efficient community-based screening for individuals at high risk of mortality is a major public health challenge. While many predictors ha...

Start4All protocol for a Bayesian cost-effectiveness model of tuberculosis screening and diagnosis in seven high burden low-income and middle-income countries.

INTRODUCTION: High costs of screening and diagnostic tests remain a major barrier to timely tuberculosis (TB) identification in resource-limited setti...

Predicting cardiovascular events from routine mammograms using machine learning.

BACKGROUND: Cardiovascular risk is underassessed in women. Many women undergo screening mammography in midlife when the risk of cardiovascular disease...

Outcomes of Artificial Intelligence Enhanced Colonoscopy in a Tertiary Clinical Setting.

BACKGROUND AND AIMS: Colonoscopies reduce colorectal cancer incidence and mortality, but challenges remain in detecting all precancerous lesions. Oper...

A Strengths, Weaknesses, Opportunities, and Threats Analysis of Generative Artificial Intelligence in Aphasia Management With Proposed Ethical Guidelines.

PURPOSE: Generative artificial intelligence (GenAI) is rapidly emerging as a transformative technology in aphasia management, necessitating judicious ...

Trust in AI-Supported Screening in General Practice Among Urban and Rural Citizens: Cross-Sectional Study.

BACKGROUND: The early detection of diseases is one of the tasks of general practice. Artificial intelligence (AI)-based technologies could be useful f...

Evaluating an AI-Enabled Mobile Mental Health Monitoring Tool Among Family Caregivers of Adults Living With Cancer: Single-Arm Feasibility and Acceptability Trial Protocol.

BACKGROUND: Psychological distress, particularly symptoms of depression and anxiety (D&A), is highly prevalent among family caregivers of individuals ...

Artificial intelligence for lung cancer: a systematic review of head‑to‑head CT, FDG PET/CT, and multimodal models across screening, staging, and prognosis.

BACKGROUND: Artificial intelligence (AI) has shown increasing potential in lung cancer imaging, particularly in detection, staging, prognosis, and rec...

Predicting risk of ascending thoracic aortic aneurysm in asymptomatic adults using machine learning.

Most patients with ascending thoracic aortic aneurysms (ATAA) remain asymptomatic until they develop fatal complications, including aortic dissection ...

From Observation to Prediction: Machine Learning Analysis of Progression of Visual loss in Nonarteritic Anterior Ischemic Optic Neuropathy.

OBJECTIVE: To determine whether combinations of modifiable clinical/systemic risk factors and structured trial variables predict early disease progres...

Artificial intelligence 12-lead electrocardiography to determine atrial fibrillation risk among UK Biobank participants with predisposing conditions.

AIMS: Artificial intelligence electrocardiography (AI-ECG) algorithms are emerging tools for identifying individuals at risk of atrial fibrillation (A...

epiGPTope: A Machine Learning-Based Epitope Generator and Classifier.

Epitopes are short antigenic peptide sequences that are recognized by antibodies or immune cell receptors. These are central to the development of imm...

Long-Term Caregivers' Perceptions and Expectations Toward the Use of Nursing Robots: A Meta-Synthesis of Qualitative Research.

This study aims to synthesize the perceptions and expectations of long-term caregivers regarding the use of nursing robots to inform strategies for en...

Smartphone-Based Portable Slit Lamp in Anterior Segment Diseases: A Narrative Review of Clinical Assessment and Integration with Artificial Intelligence.

Smartphone-based portable slit lamps are rapidly evolving from simple add-ons into practical, low-cost front-line tools for anterior segment care beyo...

Current and future use of artificial intelligence in valvular heart disease imaging.

Valvular heart disease (VHD) remains significantly underdiagnosed and undertreated. This review examines an artificial intelligence (AI)-enhanced 'spo...

Factors Associated with Machine Learning-Based Predictions of Retinal Aging Using Teleretinal Screening Images from Patients with Diabetes.

PURPOSE: To identify factors associated with accelerated retinal aging based on machine learning predictions of age using fundus images from teleretin...

The Burden of Delayed Diabetic Retinopathy Management and Use of Artificial Intelligence-Driven Screening Tools: A Systematic Literature Review.

PURPOSE: Patients with diabetic retinopathy (DR) are at risk of visual deterioration owing to systemic and financial barriers in accessing appropriate...

Screening for Tumor Microtube-Targeting Drugs Identifies PKC Modulators as Multipotent Inhibitors of Glioblastoma Progression.

UNLABELLED: Glioblastomas are incurable primary brain tumors that depend on neural-like cellular processes, tumor microtubes (TM), to invade the brain...