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The Most Effective Interventions for Classification Model Development to Predict Chat Outcomes Based on the Conversation Content in Online Suicide Prevention Chats: Machine Learning Approach.

JMIR mental health
BACKGROUND: For the provision of optimal care in a suicide prevention helpline, it is important to know what contributes to positive or negative effects on help seekers. Helplines can often be contacted through text-based chat services, which produce...

Controlled and Real-Life Investigation of Optical Tracking Sensors in Smart Glasses for Monitoring Eating Behavior Using Deep Learning: Cross-Sectional Study.

JMIR mHealth and uHealth
BACKGROUND: The increasing prevalence of obesity necessitates innovative approaches to better understand this health crisis, particularly given its strong connection to chronic diseases such as diabetes, cancer, and cardiovascular conditions. Monitor...

Real-world application of a 3D deep learning model for detecting and localizing cerebral microbleeds.

Acta neurochirurgica
BACKGROUND: Detection and localization of cerebral microbleeds (CMBs) is crucial for disease diagnosis and treatment planning. However, CMB detection is labor-intensive, time-consuming, and challenging owing to its visual similarity to mimics. This s...

Development and Internal Validation of Machine Learning to Predict Postoperative Worse Functional Status after Surgical Treatment for Thoracic Spinal Stenosis.

Medical science monitor : international medical journal of experimental and clinical research
BACKGROUND The objective of this study was to develop and validate machine learning (ML) algorithms to predict the 30-day and 6-month risk of deteriorating functional status following surgical treatment for thoracic spinal stenosis (TSS). We aimed to...

Energy expenditure prediction in preschool children: a machine learning approach using accelerometry and external validation.

Physiological measurement
This study aimed to develop convolutional neural networks (CNNs) models to predict the energy expenditure (EE) of children from raw accelerometer data. Additionally, this study sought to external validation of the CNN models in addition to the linear...

The Impact of Medical Explainable Artificial Intelligence on Nurses' Innovation Behaviour: A Structural Equation Modelling Approach.

Journal of nursing management
This study aims to investigate the influence of medical explainable artificial intelligence (XAI) on the innovation behaviour of nurses, as well as explore the dual-pathway mediating effect of AI self-efficacy and AI anxiety and organizational ethic...

Machine-learning-based evaluation of the usefulness of lactate for predicting neonatal mortality in preterm infants.

Pediatrics and neonatology
BACKGROUND: Unlike in adult and pediatric patients, the usefulness of lactate in preterm infants has not been thoroughly discussed. This study aimed to evaluate whether the lactate level in the first hours of life is an important factor associated wi...

ChatGPT and trainee performances in the management of maxillofacial patients.

Journal of stomatology, oral and maxillofacial surgery
INTRODUCTION: ChatGPT is an artificial intelligence based large language model with the ability to generate human-like response to text input, its performance has already been the subject of several studies in different fields. The aim of this study ...

Automatic Segmentation of Ultrasound-Guided Quadratus Lumborum Blocks Based on Artificial Intelligence.

Journal of imaging informatics in medicine
Ultrasound-guided quadratus lumborum block (QLB) technology has become a widely used perioperative analgesia method during abdominal and pelvic surgeries. Due to the anatomical complexity and individual variability of the quadratus lumborum muscle (Q...

Machine Learning Based Prediction of Imminent ICP Insults During Neurocritical Care of Traumatic Brain Injury.

Neurocritical care
BACKGROUND: In neurointensive care, increased intracranial pressure (ICP) is a feared secondary brain insult in traumatic brain injury (TBI). A system that predicts ICP insults before they emerge may facilitate early optimization of the physiology, w...