AIMC Topic: Humans

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Enhancing IDS for the IoMT based on advanced features selection and deep learning methods to increase the model trustworthiness.

PloS one
Information technology has significantly impacted society. IoT and its specialized variant, IoMT, enable remote patient monitoring and improve healthcare. While it contributes to improving healthcare services, it may pose significant security challen...

MRI based early Temporal Lobe Epilepsy detection using DGWO based optimized HAETN and Fuzzy-AAL Segmentation Framework (FASF).

PloS one
This work aims to promote early and accurate diagnosis of Temporal Lobe Epilepsy (TLE) by developing state-of-the-art deep learning techniques, with the goal of minimizing the consequences of epilepsy on individuals and society. Current approaches fo...

Educational improvement through machine learning: Strategic models for better PISA scores.

PloS one
In this study, in addition to traditional variables such as economic wealth or the number of books read, on which many studies have already been conducted, variables that are thought to influence student achievement and better predict success are ide...

Optimizing super-feature selection for machine learning-enhanced spectroscopic analysis in biomedical research.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
PURPOSE: Machine-learning-powered label-free infrared spectroscopic methods offer significant potential for diagnostic and biomedical applications. However, their applications have been limited by spectral noise, where critical features are often obs...

Iron metabolism and preeclampsia: new insights from bioinformatics analysis.

The journal of maternal-fetal & neonatal medicine : the official journal of the European Association of Perinatal Medicine, the Federation of Asia and Oceania Perinatal Societies, the International Society of Perinatal Obstetricians
OBJECTIVE: Preeclampsia (PE) is a multifactorial systemic pregnancy disease, in which iron metabolism and ferroptosis play significant roles during its pathogenesis. The diagnosis and prevention of PE remain urgent clinical issues that need to be add...

Posture prediction models in digital human modeling for ergonomic design: A systematic review.

Medical engineering & physics
Posture prediction models have been widely used to support ergonomic design. This systematic review critically assessed the development, validation, and applications of posture prediction models in Digital Human Modeling (DHM). Following PRISMA guide...

Integrated phenotypic and transcriptomic characterization of desmin-related cardiomyopathy in hiPSC-derived cardiomyocytes and machine learning-based classification of disease features.

European journal of cell biology
Desmin-related diseases are characterized by skeletal muscle weakness, cardiomyopathy, and respiratory dysfunction due to mutations in the desmin gene (DES), which encodes a protein essential for muscle cell integrity. This study investigates the eff...

Development and validation of peripheral blood DNA methylation signatures to predict response to biological therapy in adults with Crohn's disease (EPIC-CD): an epigenome-wide association study.

The lancet. Gastroenterology & hepatology
BACKGROUND: Biological therapeutics are widely used in Crohn's disease, with evidence of efficacy from randomised trials and real-world experience. Primary non-response is a common, poorly understood problem. We aimed to assess blood methylation as a...

Leveraging multithreading on edge computing for smart healthcare based on intelligent multimodal classification approach.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Medical digitization has been intensively developed in the last decade, leading to paving the path for computer-aided medical diagnosis research. Thus, anomaly detection based on machine and deep learning techniques has been extensively employed in h...