AIMC Topic: Artificial Intelligence
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An iterative approach to identify key predictive features of fear reactivity and fearfulness in horses (Equus caballus).
Scientific reports
Jul 9, 2025
This study extends previous findings by applying artificial intelligence (AI) methods to a larger dataset to identify key features that predict fear reactivity (i.e., immediate reaction to fear inducing stimuli) and fearfulness (i.e., a stable person...
Assessment of suicidal risk factors in young depressed persons with non-suicidal self-injury based on an artificial intelligence.
BMC psychology
Jul 8, 2025
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)
Jul 8, 2025
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...
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
Jul 8, 2025
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
Jul 8, 2025
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...
A systematic multimodal assessment of AI machine translation tools for enhancing access to critical care education internationally.
BMC medical education
Jul 8, 2025
BACKGROUND: Language barriers pose a significant barrier to expanding access to critical care education worldwide. Machine translation (MT) offers significant promise to increase accessibility to critical care content, and has rapidly evolved using n...
AI-enhanced patient-specific dosimetry in I-131 planar imaging with a single oblique view.
Scientific reports
Jul 8, 2025
This study aims to enhance the dosimetry accuracy in I planar imaging by utilizing a single oblique view and Monte Carlo (MC) validated dose point kernels (DPKs) alongside the integration of artificial intelligence (AI) for accurate dose prediction w...
Multi-task reinforcement learning and explainable AI-Driven platform for personalized planning and clinical decision support in orthodontic-orthognathic treatment.
Scientific reports
Jul 8, 2025
This study presents a novel clinical decision support platform for orthodontic-orthognathic treatment that integrates multi-task reinforcement learning with explainable artificial intelligence. The platform addresses the challenges of personalized tr...
Lossy DICOM conversion may affect AI performance.
Scientific reports
Jul 8, 2025
Many pathologies have started to digitize their glass slides. To ensure long term accessibility, it is desirable to store them in the DICOM format. Currently, many scanners initially store the images in vendor-specific formats and only provide DICOM ...
Towards fair decentralized benchmarking of healthcare AI algorithms with the Federated Tumor Segmentation (FeTS) challenge.
Nature communications
Jul 8, 2025
Computational competitions are the standard for benchmarking medical image analysis algorithms, but they typically use small curated test datasets acquired at a few centers, leaving a gap to the reality of diverse multicentric patient data. To this e...
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