AIMC Topic: Adult

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Assessing the effect of perfluoroalkyl and polyfluoroalkyl substances on cardiovascular-kidney-metabolic syndrome: Insights from an interpretable machine learning model.

The Science of the total environment
Cardiovascular-kidney-metabolic syndrome (CKM) and its association with exposure to emerging pollutants, particularly perfluoroalkyl and polyfluoroalkyl substances (PFAS), present significant challenges for environmental public health and risk predic...

Peripheral HLA-DRCD141 Classical Monocytes Predict Relapse Risk and Worsening in Multiple Sclerosis.

Neurology(R) neuroimmunology & neuroinflammation
BACKGROUND AND OBJECTIVES: Multiple sclerosis (MS) is an immune-mediated demyelinating disease of the CNS characterized by a heterogeneous disease trajectory, highlighting the need for biomarkers to predict disease activity. Current disease-monitorin...

Development of a deep learning-based automated diagnostic system (DLADS) for classifying mammographic lesions - a first large-scale multi-institutional clinical trial in Japan.

Breast cancer (Tokyo, Japan)
BACKGROUND: Recently, western countries have built evidence on mammographic artificial Intelligence-computer-aided diagnosis (AI-CADx) systems; however, their effectiveness has not yet been sufficiently validated in Japanese women. In this study, we ...

Imaging-based Surgical Site Infection Detection Using Artificial Intelligence.

Annals of surgery
OBJECTIVE: To develop an artificial intelligence-based pipeline to assess and triage patient-submitted postoperative wound images.

Multi-modal models using fMRI, urine and serum biomarkers for classification and risk prognosis in diabetic kidney disease.

Diabetes, obesity & metabolism
BACKGROUND: Functional magnetic resonance imaging (fMRI) is a powerful tool for non-invasive evaluation of micro-changes in the kidneys. This study aims to develop classification and prognostic models based on multi-modal data.

A new method for internal urinary metabolite exposure and dietary exposure association assessment of 3-MCPD and glycidol and their esters based on machine learning.

Ecotoxicology and environmental safety
3-Monochloropropane-1,2-diol (3-MCPD) and glycidol along with their esters are commonly found in chemical production, wastewater treatment, food processing, and exhibit toxicity. Accurate exposure assessment is essential for evaluating the environmen...

Two-stage ensemble learning framework for automated classification of keratoconus severity.

Computers in biology and medicine
BACKGROUND AND OBJECTIVE: Accurate staging of keratoconus (KC) is crucial for timely intervention and improving patient quality of life. Unlike prior studies that relied on traditional base machine learning (ML) models, this paper proposes a more adv...

Alterations in the functional MRI-based temporal brain organisation in individuals with obesity.

Diabetes, obesity & metabolism
AIMS: Obesity is associated with functional alterations in the brain. Although spatial organisation changes in the brains of individuals with obesity have been widely studied, the temporal dynamics in their brains remain poorly understood. Therefore,...

Pose estimation for pickleball players' kinematic analysis through MediaPipe-based deep learning: A pilot study.

Journal of sports sciences
Pickleball has gained popularity across diverse age groups. This sport has particular balls that require different hitting styles, like hitting dinks. This study focuses on introducing pickleball players' kinematic analysis through a MediaPipe-based ...

High-Performance Open-Source AI for Breast Cancer Detection and Localization in MRI.

Radiology. Artificial intelligence
Purpose To develop and evaluate an open-source deep learning model for detection and localization of breast cancer on MRI scans. Materials and Methods In this retrospective study, a deep learning model for breast cancer detection and localization was...