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SHAP-driven insights into multimodal data: behavior phase prediction for industrial safety applications.

Scientific reports
Unsafe behaviors among coal miners are a primary factor contributing to accidents, posing significant challenges for safety management. This study develops a behavior state prediction framework using artificial intelligence and machine learning (ML) ...

Anston attentional network for structured data based stroke risk prediction in smart aging.

Scientific reports
To reduce the pressure on public health services caused by the aging population, nursing homes need to predict disease risks for the elderly periodically. To improve the disease risks predicting ability of nursing homes, we designed Anston (An Attent...

Machine learning approaches overcome imbalanced clinical data for intraoral free flap monitoring.

Scientific reports
Free flap reconstruction is essential for treating intraoral defects; however, failure can lead to complex and prolonged complications. While various monitoring methods have been employed to prevent such situations, they are qualitative and sometimes...

A histomorphological atlas of resected mesothelioma discovered by self-supervised learning from 3446 whole-slide images.

Nature communications
Mesothelioma is a highly lethal and poorly biologically understood disease which presents diagnostic challenges due to its morphological complexity. This study uses self-supervised AI (Artificial Intelligence) to map the histomorphological landscape ...

Use of a Preliminary Artificial Intelligence-Based Laryngeal Cancer Screening Framework for Low-Resource Settings: Development and Validation Study.

JMIR formative research
BACKGROUND: Early-stage diagnosis of laryngeal cancer significantly improves patient survival and quality of life. However, the scarcity of specialists in low-resource settings hinders the timely review of flexible nasopharyngoscopy (FNS) videos, whi...

Evolving Health Information-Seeking Behavior in the Context of Google AI Overviews, ChatGPT, and Alexa: Interview Study Using the Think-Aloud Protocol.

Journal of medical Internet research
BACKGROUND: Online health information seeking is undergoing a major shift with the advent of artificial intelligence (AI)-powered technologies such as voice assistants and large language models (LLMs). While existing health information-seeking behavi...

Invisible Bias in GPT-4o-mini: Detecting Disparities in AI-Generated Patient Messaging.

Journal of medical systems
Artificial intelligence (AI), specifically large language models (LLM), have gained significant popularity over the last decade with increased performance and expanding applications. AI could improve the quality of patient care in medicine but hidden...

Characterization of SPTLC2 as a key driver promoting microglial activation and energy metabolism reprogramming after ischemic stroke through bulk and single-cell analyses combined with experimental validation.

Cell biology and toxicology
BACKGROUND: Ischemic stroke (IS) stands as a principal contributor to high rates of sickness and death. The condition's pathological development is complicated, featuring mechanisms like mitochondrial impairment and the activation of microglial cells...

Distributed subthreshold representation of sharp wave-ripples by hilar mossy cells.

eLife
In neural information processing, the nervous system transmits neuronal activity between layers of neural circuits, occasionally passing through small layers composed only of sparse neurons. Hippocampal hilar mossy cells (MCs) constitute such a typic...

MiThyCA: A Computational Pathology Pipeline for the Identification of Microscopic Foci of Papillary Thyroid Carcinoma-Like Nuclear Features with AI in Whole-Slide Histological Images.

Endocrine pathology
The histological identification of papillary thyroid carcinoma (PTC) is straightforward for experienced endocrine pathologists. The increase in radical thyroidectomies led to a raise in the rate of postoperative incidental subcentimeter PTC foci and ...