Preventive Care

Eye-tracking dataset of endoscopist-AI teaming during colonoscopy: Retrospective and real-time acquisition.

Recent studies have demonstrated that integrating AI into colonoscopy procedures significantly improves the adenoma detection rate (ADR) and reduces the adenoma miss rate (AMR). However, few studies address the critical issue of endoscopist-AI collaboration in real-world settings. Eye-tracking data collection is considered a promising approach to uncovering how endoscopists and AI interact and inf...

Leveraging paired mammogram views with deep learning for comprehensive breast cancer detection.

Employing two standard mammography views is crucial for radiologists, providing comprehensive insights for reliable clinical evaluations. This study introduces paired mammogram view based-network(PMVnet), a novel algorithm designed to enhance breast lesion detection by integrating relational information from paired whole mammograms, addressing the limitations of current methods. Utilizing 1,636 pr...

Proficiency, Clarity, and Objectivity of Large Language Models Versus Specialists' Knowledge on COVID-19's Impacts in Pregnancy: Cross-Sectional Pilot Study.

BACKGROUND: The COVID-19 pandemic has significantly strained health care systems globally, leading to an overwhelming influx of patients and exacerbat...

Integrating Eye Tracking With Grouped Fusion Networks for Semantic Segmentation on Mammogram Images.

Medical image segmentation has seen great progress in recent years, largely due to the development of deep neural networks. However, unlike in compute...

Screening performance and characteristics of breast cancer detected in the Mammography Screening with Artificial Intelligence trial (MASAI): a randomised, controlled, parallel-group, non-inferiority, single-blinded, screening accuracy study.

BACKGROUND: Emerging evidence suggests that artificial intelligence (AI) can increase cancer detection in mammography screening while reducing screen-...

Convolutional Neural Networks Assisted Peak Classification in Targeted LC-HRMS/MS for Equine Doping Control Screening Analyses.

Doping control screening analyses usually involve visual inspection of extracted ion chromatograms (EIC) by a trained analytical chemist, followed by ...

Development and Evaluation of a Deep Learning-Based Pulmonary Hypertension Screening Algorithm Using a Digital Stethoscope.

BACKGROUND: Despite the poor outcomes related to the presence of pulmonary hypertension, it often goes undiagnosed in part because of low suspicion an...

Fundus camera-based precision monitoring of blood vitamin A level for Wagyu cattle using deep learning.

In the wagyu industry worldwide, high-quality marbling beef is produced by promoting intramuscular fat deposition during cattle fattening stage throug...

Comparison of deep transfer learning models for classification of cervical cancer from pap smear images.

Cervical cancer is one of the most commonly diagnosed cancers worldwide, and it is particularly prevalent among women living in developing countries. ...

Hybrid transformer-based model for mammogram classification by integrating prior and current images.

BACKGROUND: Breast cancer screening via mammography plays a crucial role in early detection, significantly impacting women's health outcomes worldwide...

Cost-effectiveness of AI-based diabetic retinopathy screening in nationwide health checkups and diabetes management in Japan: A modeling study.

AIMS: We evaluated the cost-effectiveness of artificial intelligence (AI)-based diabetic retinopathy (DR) screening in Japan. This evaluation compared...

Elucidating the Mechanism of VVTT Infection Through Machine Learning and Transcriptome Analysis.

The vaccinia virus (VV) is extensively utilized as a vaccine vector in the treatment of various infectious diseases, cardiovascular diseases, immunode...

Operational Advantages of Novel Strategies Supported by Portability and Artificial Intelligence for Breast Cancer Screening in Low-Resource Rural Areas: Opportunities to Address Health Inequities and Vulnerability.

Early detection of breast cancer plays a crucial role in reducing the number of cases diagnosed at advanced stages, thereby lowering the high healthca...

From errors to excellence: the pre-analytical journey to improved quality in diagnostics. A scoping review.

This scoping review focuses on the evolution of pre-analytical errors (PAEs) in medical laboratories, a critical area with significant implications fo...

Evaluation of an AI-Based Voice Biomarker Tool to Detect Signals Consistent With Moderate to Severe Depression.

PURPOSE: Mental health screening is recommended by the US Preventive Services Task Force for all patients in areas where treatment options are availab...

Colorectal cancer detection with enhanced precision using a hybrid supervised and unsupervised learning approach.

The current work introduces the hybrid ensemble framework for the detection and segmentation of colorectal cancer. This framework will incorporate bot...

A Comparison of Prostate Cancer Screening Information Quality on Standard and Advanced Versions of ChatGPT, Google Gemini, and Microsoft Copilot: A Cross-Sectional Study.

PurposeArtificially Intelligent (AI) chatbots have the potential to produce information to support shared prostate cancer (PrCA) decision-making. Ther...

Nanobody screening and machine learning guided identification of cross-variant anti-SARS-CoV-2 neutralizing heavy-chain only antibodies.

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) continues to persist, demonstrating the risks posed by emerging infectious diseases to na...

Machine learning models for dementia screening to classify brain amyloid positivity on positron emission tomography using blood markers and demographic characteristics: a retrospective observational study.

BACKGROUND: Intracerebral amyloid β (Aβ) accumulation is considered the initial observable event in the pathological process of Alzheimer's disease (A...

Humoral and cell-mediated immune responses to COVID-19 vaccines up to 6 months post three-dose primary series in adults with inborn errors of immunity and their breakthrough infections.

PURPOSE: Many individuals with inborn errors of immunity (IEIs) have poor humoral immune (HI) vaccine responses. Only a few studies have examined spec...