AIMC Topic: Male

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Towards a Relational Understanding of Human Beings in an AI-Mediated World: A Hermeneutical Reading.

Scandinavian journal of caring sciences
INTRODUCTION: The integration of artificial intelligence (AI) into caring practices has revolutionised traditional methods, offering new possibilities while raising ethical and relational challenges. AI's ability to enhance efficiency, accuracy and a...

Improving Clinically Significant Prostate Cancer Detection with a Multimodal Machine Learning Approach: A Large-Scale Multicenter Study.

Radiology. Imaging cancer
Purpose To develop and prospectively validate a clinical and radiologic model to predict clinically significant prostate cancer (csPCa) using biparametric MRI (bpMRI). Materials and Methods Retrospective data (acquired before March 31, 2022) from 12 ...

Deep Learning-Enhanced CTA for Noninvasive Prediction of First Variceal Haemorrhage in Cirrhosis: A Multi-Centre Study.

Liver international : official journal of the International Association for the Study of the Liver
BACKGROUND AND AIMS: The first variceal haemorrhage (FVH) is a life-threatening complication of liver cirrhosis that requires timely intervention; however, noninvasive tools for accurately predicting FVH remain limited. This study aimed to develop no...

Combinative Protein Expression of Immediate Early Genes c-Fos, Arc, and Npas4 Along Aversive and Appetitive Experience-Related Neural Networks.

Hippocampus
Expression of immediate early genes (IEGs) is critical for memory formation and has been widely used to identify the neural substrate of memory traces, termed memory engram cells. Functions of IEGs have been known to be different depending on their t...

Comparison of dengue, chikungunya, and Zika among children in Nicaragua across 18 years: a single-centre, prospective cohort study.

The Lancet. Child & adolescent health
BACKGROUND: Dengue, chikungunya, and Zika are diseases of major human concern. Differential diagnosis of these three diseases is complicated in children and adolescents due to overlapping clinical features (signs, symptoms, and complete blood count r...

Alternations of Gut Microbiome and Serum Metabolome With Prolongation of the Course of Type 1 Diabetes Mellitus.

Diabetes/metabolism research and reviews
AIMS: We aimed to explore the gut microbial and serum metabolic disturbances associated with the course of type 1 diabetes mellitus (T1DM), and identify potential biomarkers for discriminating T1DM from normoglycemia individuals by machine learning.

Multifrequency Time-Dependent Deep Image Prior for Real-Time Free-Breathing Cardiac Imaging.

NMR in biomedicine
The aim of this study is to enable high temporal resolution functional cardiac imaging without breathholds or electrocardiogram (ECG) gating. Real-time MRI is essential for assessing heart function in patients with limited breathhold capacity or arrh...

Comparison of Tree-Based Machine Learning Algorithms for Classification of Livestock Breeds Based On Post-Thaw Spermatological Parameters.

Veterinary medicine and science
Reproductive efficiency is a crucial determinant of livestock productivity, with sperm quality being a key factor in successful fertilization. The quantitative assessment of spermatozoa using computer-assisted sperm analysis (CASA) yields valuable ki...

Multi-omics identification of circulating protein biomarkers for intervertebral disc degeneration using Mendelian randomization and scRNA-seq.

Clinical rheumatology
BACKGROUND: Intervertebral disc degeneration (IVDD) is a primary cause of chronic low back pain, significantly impacting quality of life and healthcare systems globally. Despite its prevalence, the molecular mechanisms underlying IVDD remain unclear,...

Machine Learning-Based Flap Takeback Prediction Modeling: Theory for a Real-Time, Patient-Specific Postoperative Flap Monitoring and Alert System.

Microsurgery
BACKGROUND: Postoperative free flap monitoring is crucial yet taxing, requiring frequent and often subjective assessments to detect early signs of compromise. The present study aims to develop a machine learning model to predict the risk of flap take...