AIMC Topic: Humans

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Enhancing multiclass COVID-19 prediction with ESN-MDFS: Extreme smart network using mean dropout feature selection technique.

PloS one
Deep learning and artificial intelligence offer promising tools for improving the accuracy and efficiency of diagnosing various lung conditions using portable chest x-rays (CXRs). This study explores this potential by leveraging a large dataset conta...

Data augmentation via warping transforms for modeling natural variability in the corneal endothelium enhances semi-supervised segmentation.

PloS one
Image segmentation of the corneal endothelium with deep convolutional neural networks (CNN) is challenging due to the scarcity of expert-annotated data. This work proposes a data augmentation technique via warping to enhance the performance of semi-s...

Artificial Intelligence-based Assessment of Facial Symmetry Aesthetics of Saudi Arabian Population.

Facial plastic surgery : FPS
The purpose of this study is to investigate facial symmetry aesthetics (FSA) in the Saudi Arabian population using artificial intelligence (AI).Two hundred and ten people from a range of demographic backgrounds participated in an observational cross-...

Development and external validation of a machine learning model to predict diabetic nephropathy in T1DM patients in the real-world.

Acta diabetologica
AIMS: Studies on machine learning (ML) for the prediction of diabetic nephropathy (DN) in type 1 diabetes mellitus (T1DM) patients are rare. This study focused on the development and external validation of an explainable ML model to predict the risk ...

High-precision MRI of liver and hepatic lesions on gadoxetic acid-enhanced hepatobiliary phase using a deep learning technique.

Japanese journal of radiology
PURPOSE: The purpose of this study was to investigate whether the high-precision magnetic resonance (MR) sequence using modified Fast 3D mode wheel and Precise IQ Engine (PIQE), that was collected in a wheel shape with sequential data filling in the ...

Exploring the potential of large language models in identifying metabolic dysfunction-associated steatotic liver disease: A comparative study of non-invasive tests and artificial intelligence-generated responses.

Liver international : official journal of the International Association for the Study of the Liver
BACKGROUND AND AIMS: This study sought to assess the capabilities of large language models (LLMs) in identifying clinically significant metabolic dysfunction-associated steatotic liver disease (MASLD).

Impact of upper extremity robotic rehabilitation on respiratory parameters, functional capacity and dyspnea in patients with stroke: a randomized controlled study.

Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology
BACKGROUND: Stroke leads to reduced mobility and functional capacity, also negatively affects respiratory functions and muscle strength.

Self-Attention Mechanisms-Based Laryngoscopy Image Classification Technique for Laryngeal Cancer Detection.

Head & neck
BACKGROUND: The early diagnosis of laryngeal cancer (LCA) is crucial for prognosis, driving our search for an accurate, precise, and sensitive deep learning model to assist in LCA detection.

Subjective well-being of children with special educational needs: Longitudinal predictors using machine learning.

Applied psychology. Health and well-being
Children with special educational needs (SEN) are a diverse group facing numerous challenges related to well-being and mental health. Understanding the predictors of well-being in this population requires the incorporation of diverse factors along wi...

Applying machine learning to understand the role of social-emotional skills on subjective well-being and physical health.

Applied psychology. Health and well-being
Social-emotional skills are vital for individual development, yet research on which skills most effectively promote students' mental and physical health, particularly from a global perspective, remains limited. This study aims to address this gap by ...