AIMC Topic: Humans

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Evaluation of AI-based auto-contouring tools in radiotherapy: A single-institution study.

Journal of applied clinical medical physics
BACKGROUND: Accurate delineation of organs at risk (OARs) is crucial yet time-consuming in the radiotherapy treatment planning workflow. Modern artificial intelligence (AI) technologies had made automation of OAR contouring feasible. This report deta...

Guardian-BERT: Early detection of self-injury and suicidal signs with language technologies in electronic health reports.

Computers in biology and medicine
Mental health disorders, including non-suicidal self-injury (NSSI) and suicidal behavior, represent a growing global concern. Early detection of these conditions is crucial for timely intervention and prevention of adverse outcomes. In this study, we...

From social media to artificial intelligence: improving research on digital harms in youth.

The Lancet. Child & adolescent health
In this Personal View, we critically evaluate the limitations and underlying challenges of existing research into the negative mental health consequences of internet-mediated technologies on young people. We argue that identifying and proactively add...

National survey on data governance and digital surgery: Challenges and opportunities for surgeons in the era of artificial intelligence.

Cirugia espanola
INTRODUCTION: This study evaluates the knowledge of Spanish surgeons regarding data governance and Digital Surgery, their usage, errors, and training deficiencies, as well as differences in knowledge between those who perform robotic surgery and thos...

Large language models vs human for classifying clinical documents.

International journal of medical informatics
BACKGROUND: Accurate classification of medical records is crucial for clinical documentation, particularly when using the 10th revision of the International Classification of Diseases (ICD-10) coding system. The use of machine learning algorithms and...

ATEDU-NET: An Attention-Embedded Deep Unet for multi-disease diagnosis in chest X-ray images, breast ultrasound, and retina fundus.

Computers in biology and medicine
In image segmentation for medical image analysis, effective upsampling is crucial for recovering spatial information lost during downsampling. This challenge becomes more pronounced when dealing with diverse medical image modalities, which can signif...

Automated model discovery for tensional homeostasis: Constitutive machine learning in growth and remodeling.

Computers in biology and medicine
We present a built-in physics neural network architecture, known as inelastic Constitutive Artificial Neural Network (iCANN), to discover the inelastic phenomenon of tensional homeostasis. In this course, identifying the optimal model and material pa...

Predicting lower body joint moments and electromyography signals using ground reaction forces during walking and running: An artificial neural network approach.

Gait & posture
BACKGROUND: This study leverages Artificial Neural Networks (ANNs) to predict lower limb joint moments and electromyography (EMG) signals from Ground Reaction Forces (GRF), providing a novel perspective on human gait analysis. This approach aims to e...

Comparative Analysis of Recurrent Neural Networks with Conjoint Fingerprints for Skin Corrosion Prediction.

Journal of chemical information and modeling
Skin corrosion assessment is an essential toxicity end point that addresses safety concerns for topical dosage forms and cosmetic products. Previously, skin corrosion assessments required animal testing; however, differences in skin architecture and ...

Is artificial intelligence an opportunity or a threat in nursing care?: An in-depth phenomenological study.

Archives of psychiatric nursing
INTRODUCTION: In the contemporary landscape, the use of artificial intelligence (AI) in nursing care has sparked ongoing debates regarding its merits and drawbacks.