AIMC Topic: Humans

Clear Filters Showing 9211 to 9220 of 95995 articles

Deep Learning Methods in the Imaging of Hepatic and Pancreaticobiliary Diseases.

Journal of clinical gastroenterology
Reports indicate a growing role for artificial intelligence (AI) in the evaluation of pancreaticobiliary and hepatic conditions. A key focus is differentiating between benign and malignant lesions, which is crucial for treatment decisions. AI improve...

IT: An interpretable transformer model for Alzheimer's disease prediction based on PET/MR images.

NeuroImage
Alzheimer's disease (AD) represents a significant challenge due to its progressive neurodegenerative impact, particularly within an aging global demographic. This underscores the critical need for developing sophisticated diagnostic tools for its ear...

Using machine learning to investigate the influence of the prenatal chemical exposome on neurodevelopment of young children.

Neurotoxicology
Research investigating the prenatal chemical exposome and child neurodevelopment has typically focused on a limited number of chemical exposures and controlled for sociodemographic factors and maternal mental health. Emerging machine learning approac...

Engineering TCR-controlled fuzzy logic into CAR T cells enhances therapeutic specificity.

Cell
Chimeric antigen receptor (CAR) T cell immunotherapy represents a breakthrough in the treatment of hematological malignancies, but poor specificity has limited its applicability to solid tumors. By contrast, natural T cells harboring T cell receptors...

Leveraging deep learning for improving parameter extraction from perfusion MR images: A narrative review.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
BACKGROUND: Perfusion magnetic resonance imaging (MRI) is a non-invasive technique essential for assessing tissue microcirculation and perfusion dynamics. Various perfusion MRI techniques like Dynamic Contrast-Enhanced (DCE), Dynamic Susceptibility C...

Extreme Weather, Vulnerable Populations, and Mental Health: The Timely Role of AI Interventions.

International journal of environmental research and public health
Environmental disasters are becoming increasingly frequent and severe, disproportionately impacting vulnerable populations who face compounded risks due to intersectional factors such as gender, socioeconomic status, rural residence, and cultural ide...

Artificial Intelligence-Driven Biological Age Prediction Model Using Comprehensive Health Checkup Data: Development and Validation Study.

JMIR aging
BACKGROUND: The global increase in life expectancy has not shown a similar rise in healthy life expectancy. Accurate assessment of biological aging is crucial for mitigating diseases and socioeconomic burdens associated with aging. Current biological...

Optimized classification of dental implants using convolutional neural networks and pre-trained models with preprocessed data.

BMC oral health
OBJECTIVE: This study evaluates the performance of various classifiers and pre-trained models for dental implant state classification using preprocessed radiography images with masks.

Explainable AI for enhanced accuracy in malaria diagnosis using ensemble machine learning models.

BMC medical informatics and decision making
BACKGROUND: Malaria, an infectious disease caused by protozoan parasites belonging to the Plasmodium genus, remains a significant public health challenge, with African regions bearing the heaviest burden. Machine learning techniques have shown great ...

Neural network analysis as a novel skin outcome in a trial of belumosudil in patients with systemic sclerosis.

Arthritis research & therapy
BACKGROUND: The modified Rodnan skin score (mRSS), a measure of systemic sclerosis (SSc) skin thickness, is agnostic to inflammation and vasculopathy. Previously, we demonstrated the potential of neural network-based digital pathology applied to SSc ...