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DeepPerfusion: A comprehensible two-branched deep learning architecture for high-precision blood volume pulse extraction based on imaging photoplethysmography.

Computers in biology and medicine
Imaging photoplethysmography (iPPG) is a contactless approach for the extraction of the blood volume pulsation (BVP). Analyzing the small intensity changes resulting from fluctuations in light absorption in upper skin layers enables BVP extraction. I...

BrainAGE latent representation clustering is associated with longitudinal disease progression in early-onset Alzheimer's disease.

Journal of neuroradiology = Journal de neuroradiologie
INTRODUCTION: Early-onset Alzheimer's disease (EOAD) population is a clinically, genetically and pathologically heterogeneous condition. Identifying biomarkers related to disease progression is crucial for advancing clinical trials and improving ther...

A Novel Two-step Classification Approach for Differentiating Bone Metastases From Benign Bone Lesions in SPECT/CT Imaging.

Academic radiology
RATIONALE AND OBJECTIVES: This study aims to develop and validate a novel two-step deep learning framework for the automated detection, segmentation, and classification of bone metastases in SPECT/CT imaging, accurately distinguishing malignant from ...

SPACE: Subregion Perfusion Analysis for Comprehensive Evaluation of Breast Tumor Using Contrast-Enhanced Ultrasound-A Retrospective and Prospective Multicenter Cohort Study.

Ultrasound in medicine & biology
OBJECTIVE: To develop a dynamic contrast-enhanced ultrasound (CEUS)-based method for segmenting tumor perfusion subregions, quantifying tumor heterogeneity, and constructing models for distinguishing benign from malignant breast tumors.

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.