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YOLOv11-Based quantification and temporal analysis of repetitive behaviors in deer mice.

Neuroscience
Detailed temporal dynamics of deer mouse (Peromyscus maniculatus bairdii) behavior remain poorly characterized. This study presents an integrated automated system combining YOLOv11 deep learning for direct behavior classification, post-processing for...

Neuroimaging pattern interactions for suicide risk in depression captured by ensemble learning over transcriptome-defined parcellation.

Progress in neuro-psychopharmacology & biological psychiatry
BACKGROUND: For suicide in major depression disorder, it is urgent to seek for a reliable neuroimaging biomarker with interpretable links to molecular tissue signatures. Accordingly, we developed an ensemble learning scheme over transcriptome-defined...

Blood-based proteomic profiling identifies OSMR as a novel biomarker of AML outcomes.

Blood
Inflammation is increasingly recognized as a critical factor in acute myeloid leukemia (AML) pathogenesis. We performed blood-based proteomic profiling of 251 inflammatory proteins in 543 patients with newly diagnosed AML. Using a machine learning mo...

Prediction of bacterial and fungal bloodstream infections using machine learning in patients undergoing chemotherapy.

European journal of cancer (Oxford, England : 1990)
PURPOSE: This study aimed to develop a machine learning (ML) model to predict bloodstream infection (BSI) in chemotherapy patients.

Representation of locomotive action affordances in human behavior, brains, and deep neural networks.

Proceedings of the National Academy of Sciences of the United States of America
To decide how to move around the world, we must determine which locomotive actions (e.g., walking, swimming, or climbing) are afforded by the immediate visual environment. The neural basis of our ability to recognize locomotive affordances is unknown...

Microbial dysbiosis and its diagnostic potential in androgenetic alopecia: insights from multi-kingdom sequencing and machine learning.

mSystems
Androgenetic alopecia (AGA), the most common form of hair loss, has been linked to dysbiosis of the scalp microbiome. In this study, we collected microbiome samples from the frontal baldness and occipital regions of patients with varying stages of AG...

Machine Learning Prediction of Pancreatitis Risk With Antithyroid Drugs: A Nationwide Retrospective Observational Study.

The Journal of clinical endocrinology and metabolism
BACKGROUND: In recent years, there has been increasing data showing that the risk of acute pancreatitis (AP) is increased in patients using methimazole (MMI). The aim of this population-based study was to investigate the association between drugs use...

Leveraging Artificial Intelligence for Digital Symptom Management in Oncology: The Development of CRCWeb.

JMIR cancer
Digital health interventions offer promise for scalable and accessible health care, but access is still limited by some participatory challenges, especially for disadvantaged families facing limited health literacy, language barriers, low income, or ...

Artificial Intelligence for Patient Support: Assessing Retrieval-Augmented Generation for Answering Postoperative Rhinoplasty Questions.

Aesthetic surgery journal
BACKGROUND: Although artificial intelligence (AI) is revolutionizing healthcare, inaccurate or incomplete information from pretrained large language models (LLMs) like ChatGPT poses significant risks to patient safety. Retrieval-augmented generation ...

AI-powered evaluation of lung function for diagnosis of interstitial lung disease.

Thorax
BACKGROUND: The diagnosis of interstitial lung disease (ILD) can pose a challenge as the pulmonary function test (PFT) is only minimally affected at the onset. To improve early diagnosis, this study aims to explore the potential of artificial intelli...