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Prevention of medical errors

Latest AI and machine learning research in prevention of medical errors for healthcare professionals.

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FedPD: Defending federated prototype learning against backdoor attacks.

Federated Learning (FL) is an efficient, distributed machine learning paradigm that enables multiple...

Integrating AI-driven wearable devices and biometric data into stroke risk assessment: A review of opportunities and challenges.

Stroke is a leading cause of morbidity and mortality worldwide, and early detection of risk factors ...

From Code to Clots: Applying Machine Learning to Clinical Aspects of Venous Thromboembolism Prevention, Diagnosis, and Management.

The high incidence of venous thromboembolism (VTE) globally and the morbidity and mortality burden a...

Natural compounds for Alzheimer's prevention and treatment: Integrating SELFormer-based computational screening with experimental validation.

BACKGROUND: This study aimed to develop and apply a novel computational pipeline combining SELFormer...

A Pathological Diagnosis Method for Fever of Unknown Origin Based on Multipath Hierarchical Classification: Model Design and Validation.

BACKGROUND: Fever of unknown origin (FUO) is a significant challenge for the medical community due t...

Advancing personalised care in atrial fibrillation and stroke: The potential impact of AI from prevention to rehabilitation.

Atrial fibrillation (AF) is a complex condition caused by various underlying pathophysiological diso...

Machine Learning and Deep Learning Approaches for Arabic Sign Language Recognition: A Decade Systematic Literature Review.

Sign language (SL) is a means of communication that is used to bridge the gap between the deaf, hear...

Artificial Intelligence: A Challenge to Scientific Communication.

Recent years have seen formidable advances in artificial intelligence. Developments include a large ...

Machine-learning-based identification of patients with IgA nephropathy using a computerized medical billing database.

The billing database of the universal healthcare system in Japan potentially includes large-cohort d...

Medical Federated Model With Mixture of Personalized and Shared Components.

Although data-driven methods usually have noticeable performance on disease diagnosis and treatment,...

Artificial intelligence and pediatric surgery: where are we?

Here, we explore the transformative effects of artificial intelligence (AI) and large language model...

Using Artificial Intelligence to Detect Risk of Family Violence: Protocol for a Systematic Review and Meta-Analysis.

BACKGROUND: Despite the implementation of prevention strategies, family violence continues to be a p...

STAR-RL: Spatial-Temporal Hierarchical Reinforcement Learning for Interpretable Pathology Image Super-Resolution.

Pathology image are essential for accurately interpreting lesion cells in cytopathology screening, b...

UrologiQ: AI-based accurate detection, measurement and reporting of stones in CT-KUB scans.

Kidney stone disease is becoming increasingly common worldwide, with its prevalence increasing annua...

-targeted AI-driven vaccines: a paradigm shift in gastric cancer prevention.

, a globally prevalent pathogen Group I carcinogen, presents a formidable challenge in gastric cance...

FedDBL: Communication and Data Efficient Federated Deep-Broad Learning for Histopathological Tissue Classification.

Histopathological tissue classification is a fundamental task in computational pathology. Deep learn...

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