Prevention of medical errors

Flexible Conformally Bioadhesive MXene Hydrogel Electronics for Machine Learning-Facilitated Human-Interactive Sensing.

Wearable epidermic electronics assembled from conductive hydrogels are attracting various research a...

Arrhythmia detection by the graph convolution network and a proposed structure for communication between cardiac leads.

One of the most common causes of death worldwide is heart disease, including arrhythmia. Today, scie...

Classification of the quality of canine and feline ventrodorsal and dorsoventral thoracic radiographs through machine learning.

Thoracic radiographs are an essential diagnostic tool in companion animal medicine and are frequentl...

Large language models for preventing medication direction errors in online pharmacies.

Errors in pharmacy medication directions, such as incorrect instructions for dosage or frequency, ca...

Temporal Relationship-Aware Treadmill Exercise Test Analysis Network for Coronary Artery Disease Diagnosis.

The treadmill exercise test (TET) serves as a non-invasive method for the diagnosis of coronary arte...

Model fusion for predicting unconventional proteins secreted by exosomes using deep learning.

Unconventional secretory proteins (USPs) are vital for cell-to-cell communication and are necessary ...

[ScreenGPT - The opportunities and limitations of artificial intelligence in primary, secondary and tertiary prevention].

Prevention of Leakage in Machine Learning Prediction for Polymer Composite Properties.

Machine learning (ML) has facilitated property prediction for intricate materials by integrating mat...

Application of artificial intelligence technology in monitoring students' health: Preliminary results of Syiah Kuala Integrated Medical Monitoring (SKIMM).

Health promoting university is a holistic approach to health that uses higher education settings to ...

Machine learning-driven diagnostic signature provides new insights in clinical management of hypertrophic cardiomyopathy.

AIMS: In an era of evolving diagnostic possibilities, existing diagnostic systems are not fully suff...

Anatomically aware dual-hop learning for pulmonary embolism detection in CT pulmonary angiograms.

Pulmonary Embolisms (PE) represent a leading cause of cardiovascular death. While medical imaging, t...

Artificial intelligence in multiple sclerosis management: Challenges in a new era.

Multiple sclerosis poses diagnostic and therapeutic challenges for healthcare professionals, with a ...

Physiological data for affective computing in HRI with anthropomorphic service robots: the AFFECT-HRI data set.

In human-human and human-robot interaction, the counterpart influences the human's affective state. ...

Artificial intelligence and mental capacity legislation: Opening Pandora's modem.

People with impaired decision-making capacity enjoy the same rights to access technology as people w...

Explainable artificial intelligence models for predicting risk of suicide using health administrative data in Quebec.

Suicide is a complex, multidimensional event, and a significant challenge for prevention globally. A...

Adequacy of prostate cancer prevention and screening recommendations provided by an artificial intelligence-powered large language model.

PURPOSE: We aimed to assess the appropriateness of ChatGPT in providing answers related to prostate ...

AI-Generated Draft Replies Integrated Into Health Records and Physicians' Electronic Communication.

IMPORTANCE: Timely tests are warranted to assess the association between generative artificial intel...

Evaluations of artificial intelligence and machine learning algorithms in neurodiagnostics.

This article evaluates the ethical implications of utilizing artificial intelligence (AI) algorithms...

Human-robot facial coexpression.

Large language models are enabling rapid progress in robotic verbal communication, but nonverbal com...

Machine-based learning of multidimensional data in bipolar disorder - pilot results.

INTRODUCTION: Owing to the heterogenic picture of bipolar disorder, it takes approximately 8.8 years...

No shortcuts: False economy prevention during artificial intelligence implementation in rural Australian health care.