AIMC Topic: Male

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Deep Learning Radiomics Analysis of CT Imaging for Differentiating Between Crohn's Disease and Intestinal Tuberculosis.

Journal of imaging informatics in medicine
This study aimed to develop and evaluate a CT-based deep learning radiomics model for differentiating between Crohn's disease (CD) and intestinal tuberculosis (ITB). A total of 330 patients with pathologically confirmed as CD or ITB from the First Af...

Improving Image Quality and Nodule Characterization in Ultra-low-dose Lung CT with Deep Learning Image Reconstruction.

Academic radiology
RATIONALE AND OBJECTIVE: To investigate the influence of the deep learning image reconstruction (DLIR) on the image quality and quantitative analysis of pulmonary nodules under ultra-low dose lung CT conditions.

Interpretable and Intuitive Machine Learning Approaches for Predicting Disability Progression in Relapsing-Remitting Multiple Sclerosis Based on Clinical and Gray Matter Atrophy Indicators.

Academic radiology
RATIONALE AND OBJECTIVES: To investigate whether clinical and gray matter (GM) atrophy indicators can predict disability in relapsing-remitting multiple sclerosis (RRMS) and to enhance the interpretability and intuitiveness of a predictive machine le...

Enhancing neural encoding models for naturalistic perception with a multi-level integration of deep neural networks and cortical networks.

Science bulletin
Cognitive neuroscience aims to develop computational models that can accurately predict and explain neural responses to sensory inputs in the cortex. Recent studies attempt to leverage the representation power of deep neural networks (DNNs) to predic...

Development of a microultrasound-based nomogram to predict extra-prostatic extension in patients with prostate cancer undergoing robot-assisted radical prostatectomy.

Urologic oncology
OBJECTIVES: To develop a microultrasound-based nomogram including clinicopathological parameters and microultrasound findings to predict the presence of extra-prostatic extension and guide the grade of nerve-sparing.

Decoding emotions: Exploring the validity of sentiment analysis in psychotherapy.

Psychotherapy research : journal of the Society for Psychotherapy Research
OBJECTIVE: Given the importance of emotions in psychotherapy, valid measures are essential for research and practice. As emotions are expressed at different levels, multimodal measurements are needed for a nuanced assessment. Natural Language Process...

The Effects of Combined Virtual Reality Exercises and Robot Assisted Gait Training on Cognitive Functions, Daily Living Activities, and Quality of Life in High Functioning Individuals With Subacute Stroke.

Perceptual and motor skills
Stroke is a global health concern causing significant mortality. Survivors face physical, cognitive, and emotional challenges, affecting their life satisfaction and social participation. Robot-assisted gait training with virtual reality, like Lokomat...

Comparison of an Ensemble of Machine Learning Models and the BERT Language Model for Analysis of Text Descriptions of Brain CT Reports to Determine the Presence of Intracranial Hemorrhage.

Sovremennye tekhnologii v meditsine
UNLABELLED: is to train and test an ensemble of machine learning models, as well as to compare its performance with the BERT language model pre-trained on medical data to perform simple binary classification, i.e., determine the presence/absence of ...

Investigation of the adaptation of older adults to online learning and artificial intelligence.

Revista espanola de geriatria y gerontologia
PURPOSE: The purpose of this study was to investigate the adaptation of older adults, to online learning and artificial intelligence.

PedBotLab: A Novel Video Game-Based Robotic Ankle Platform Created for Therapeutic Exercise for Children With Neurological Impairments.

Physical & occupational therapy in pediatrics
AIMS: Assess the potential benefits of using PedBotLab, a clinic based robotic ankle platform with integrated video game software, to improve ankle active and passive range of motion, strength, selective motor control, gait efficiency, and balance.