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Shall we call for a doctor? How to build trust toward AI in healthcare: Insights from a Polish cross-sectional preference study.

Health policy (Amsterdam, Netherlands)
OBJECTIVES: This research aimed to investigate key success factors for the adoption of AI-driven health technologies, particularly in healthcare ecosystems of low digital literacy, such as Poland.

Automated quantification of T1 and T2 relaxation times in liver mpMRI using deep learning: a sequence-adaptive approach.

European radiology experimental
OBJECTIVES: To evaluate a deep learning sequence-adaptive liver multiparametric MRI (mpMRI) assessment with validation in different populations using total and segmental T1 and T2 relaxation time maps.

Automated analysis of mouse rearing using deep learning.

Journal of pharmacological sciences
Rodent rearing behavior is frequently assessed as an indicator of anxiety and exploratory tendencies. This study developed a convolutional recurrent neural network (CRNN) model to detect mouse rearing using overhead videos. Behavioral data from C57BL...

Mucosal immune responses and intestinal microbiome associations in wild spotted hyenas (Crocuta crocuta).

Communications biology
Little is known about host-gut microbiome interactions within natural populations at the intestinal mucosa, the primary interface. We investigate associations between the intestinal microbiome and mucosal immune measures while controlling for host, s...

Gut microbiota alterations are linked to COVID-19 severity in North African and European populations.

NPJ biofilms and microbiomes
Although COVID-19 primarily affects the respiratory system, many patients experience gastrointestinal symptoms, suggesting a role for the gut microbiota in disease pathogenesis. To explore this, we performed shotgun metagenomic sequencing on stool sa...

Adaptive weighted dual MAML: Proposing a novel method for the automated diagnosis of partial sleep deprivation.

PloS one
INTRODUCTION: Sleep disorders significantly disrupt normal sleep patterns and pose serious health risks. Traditional diagnostic methods, such as questionnaires and polysomnography, often require extensive time and are susceptible to errors. This high...

Same-model and cross-model variability in knee cartilage thickness measurements using 3D MRI systems.

PloS one
PURPOSE: Magnetic Resonance Imaging (MRI) based three-dimensional analysis of knee cartilage has evolved to become fully automatic. However, when implementing these measurements across multiple clinical centers, scanner variability becomes a critical...

Clinical feasibility of AI Doctors: Evaluating the replacement potential of large language models in outpatient settings for central nervous system tumors.

International journal of medical informatics
BACKGROUND AND OBJECTIVES: The treatment of central nervous system (CNS) tumors is complex and resource-intensive, with higher mortality in underserved regions. Large language models (LLMs) show promise in medical support, but their real-world perfor...

NeuroEmo: A neuroimaging-based fMRI dataset to extract temporal affective brain dynamics for Indian movie video clips stimuli using dynamic functional connectivity approach with graph convolution neural network (DFC-GCNN).

Computers in biology and medicine
FMRI, a non-invasive neuroimaging technique, can detect emotional brain activation patterns. It allows researchers to observe functional changes in the brain, making it a valuable tool for emotion recognition. For improved emotion recognition systems...