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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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Showing 1513-1533 of 5,107 articles
Enhancing the Reliability of Resting ECGs via Deep Learning–Driven Motion Artifact Detection

This study presents a novel two-stage framework to enhance the reliability of resting electrocardiog...

Validation of an AI-powered mobile application for personalizing medical note explanations

Almost half of adults struggle to understand written health information, making medical communicatio...

An Artificial Intelligence Approach to Augmentative and Assistive Communication for Patients with Amyotrophic Lateral Sclerosis

Amyotrophic Lateral Sclerosis (ALS) progressively impairs motor functions, making communication incr...

AI-Simulated Clinical Consultations: Assessing the Potential of ChatGPT to Support Medical Training

Simulated medical scenarios are useful for evaluating and developing clinical competencies but sched...

Improving Doctor-Patient Communication Using Large Language Models - Results from an Experimental Study

Medical jargon poses significant barriers to patient comprehension of healthcare information, potent...

Enhancing MRI Safety: Real-Time Thermal Imaging Integrated with Deep Learning for Burn Prevention

Radiofrequency (RF)-induced burns are the most common MRI-related adverse event. Standard safety pra...

PREFER-IT: A transdisciplinary co-created framework to realise inclusive medical AI

Artificial intelligence (AI) in healthcare holds transformative potential but risks exacerbating exi...

Patient-Reported Challenges in Lymphoma Diagnosis: Analysis of Online Forum Narratives Using Artificial Intelligence

Lymphoma diagnosis remains challenging due to diverse subtypes and nonspecific presentations. While ...

Predicting Carbapenem Resistance in Hospitalized Patients Using Machine Learning: A Retrospective Analysis of the MIMIC-III Database

Carbapenem-resistant Gram-negative bacteria (CR-GNB) represent a major health challenge due to limit...

Machine learning-driven prediction of opioid and stimulant-related drug overdose fatalities: Analysis of the potential fourth wave

Between 2010 and 2021, fentanyl and stimulants co-involved deaths increased from 0.6% to 32.3% of al...

TRUSTING: An International Multicenter Observational Study of Speech-Based Relapse Prediction in Psychosis Using Explainable AI

The course of psychotic disorders typically involves relapses. Early warning signs vary between indi...

Communication Efficient Cooperative Edge AI via Event-Triggered Computation Offloading

Rare events, despite their infrequency, often carry critical information and require immediate att...

Deep learning-enhanced signal detection for communication systems.

Traditional communication signal detection heavily relies on manually designed features, making it d...

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