AIMC Topic: Humans

Clear Filters Showing 5681 to 5690 of 95995 articles

Drp1 Proteins Released from Hydrolysis-Driven Scaffold Disassembly Trigger Nucleotide-Dependent Membrane Remodeling to Promote Scission.

Journal of the American Chemical Society
Dynamin-related protein (Drp1) drives mitochondrial fission, dysregulation of which leads to neurodegenerative, metabolic, and apoptotic disorders. The precise mechanism of fission completion is unclear. One prevailing model is based on GTP-driven o...

Dynamin-like Proteins Combine Mechano-constriction and Membrane Remodeling to Enable Two-Step Mitochondrial Fission via a "Snap-through" Instability.

Journal of the American Chemical Society
Mitochondrial fission is controlled by dynamin-like proteins, the dysregulation of which is correlated with diverse diseases. Fission dynamin-like proteins are GTP hydrolysis-driven mechanoenzymes that self-oligomerize into helical structures that co...

OMT and tensor SVD-based deep learning model for segmentation and predicting genetic markers of glioma: A multicenter study.

Proceedings of the National Academy of Sciences of the United States of America
Glioma is the most common primary malignant brain tumor and preoperative genetic profiling is essential for the management of glioma patients. Our study focused on tumor regions segmentation and predicting the World Health Organization (WHO) grade, i...

Assessing the Accuracy of ChatGPT in Appropriately Triaging Common Postoperative Concerns Regarding Mohs Micrographic Surgery.

JMIR dermatology
Artificial intelligence (AI) is increasingly integrated into health care, offering potential benefits in patient education, triage, and administrative efficiency. This study evaluates AI-driven dialogue interfaces within an electronic health record a...

Assessment of suicidal risk factors in young depressed persons with non-suicidal self-injury based on an artificial intelligence.

BMC psychology
INTRODUCTION: The role of non-suicidal self-injury (NSSI) in the suicide process of people with major depressive disorder(MDD) remains controversial. Therefore, the purpose of this study was to investigate the role NSSI plays in suicide risk in peopl...

Implementing Artificial Intelligence in Critical Care Medicine: a consensus of 22.

Critical care (London, England)
Artificial Intelligence (AI) is rapidly transforming the landscape of critical care, offering opportunities for enhanced diagnostic precision and personalized patient management. However, its integration into ICU clinical practice presents significan...

MRDDA: a multi-relational graph neural network for drug-disease association prediction.

Journal of translational medicine
BACKGROUND: Drug repositioning offers a promising avenue for accelerating drug development and reducing costs. Recently, computational repositioning approaches have gained attraction for identifying potential drug-disease associations (DDAs). Biologi...

A novel method to predict the haemoglobin concentration after kidney transplantation based on machine learning: prediction model establishment and method optimization.

BMC medical informatics and decision making
BACKGROUND: Anaemia is a common complication after kidney transplantation, and the haemoglobin concentration is one of the main criteria for identifying anaemia. Moreover, artificial intelligence methods have developed rapidly in recent years, are wi...

Artificial intelligence-driven discovery of YH395A: A novel TGFβR1 inhibitor with potent anti-tumor activity against triple-negative breast cancer.

Cell communication and signaling : CCS
Characterized by high malignancy and limited treatment efficacy, triple-negative breast cancer (TNBC) remains a clinically challenging subtype within breast cancer classifications, marked by rapid progression and high mortality. Abnormal activation o...

Streamlining medical software development with CARE lifecycle and CARE agent: an AI-driven technology readiness level assessment tool.

BMC medical informatics and decision making
BACKGROUND: Developing medical software requires navigating complex regulatory, ethical, and operational challenges. A comprehensive framework that supports both technical maturity and clinical safety is essential for effective artificial intelligenc...