Emergency Medicine

Deep-Learning Approach for Tissue Classification using Acoustic Waves during Ablation with an Er:YAG Laser (Updated)

Today's mechanical tools for bone cutting (osteotomy) cause mechanical trauma that prolongs the healing process. Medical device manufacturers aim to minimize this trauma, with minimally invasive surgery using laser cutting as one innovation. This method ablates tissue using laser light instead of mechanical tools, reducing post-surgery healing time. A reliable feedback system is crucial during l...

Cold-start Recommendation by Personalized Embedding Region Elicitation

Rating elicitation is a success element for recommender systems to perform well at cold-starting, in which the systems need to recommend items to a newly arrived user with no prior knowledge about the user's preference. Existing elicitation methods employ a fixed set of items to learn the user's preference and then infer the users' preferences on the remaining items. Using a fixed seed set can l...

[Minimally invasive intelligent innovative technologies in foot and ankle surgery: development status and prospects].

The rapid development of technology has ushered in a new era of minimally invasive and intelligent surgery.Minimally invasive surgeries, such as small...

Force/position tracking control of fracture reduction robot based on nonlinear disturbance observer and neural network.

BACKGROUND: For the fracture reduction robot, the position tracking accuracy and compliance are affected by dynamic loads from muscle stretching, unce...

Assessing the readability, reliability, and quality of artificial intelligence chatbot responses to the 100 most searched queries about cardiopulmonary resuscitation: An observational study.

This study aimed to evaluate the readability, reliability, and quality of responses by 4 selected artificial intelligence (AI)-based large language mo...

BioBERT-based Deep Learning and Merged ChemProt-DrugProt for Enhanced Biomedical Relation Extraction

This paper presents a methodology for enhancing relation extraction from biomedical texts, focusing specifically on chemical-gene interactions. Leve...

Automated stratification of trauma injury severity across multiple body regions using multi-modal, multi-class machine learning models.

OBJECTIVE: The timely stratification of trauma injury severity can enhance the quality of trauma care but it requires intense manual annotation from c...

Using Computer Vision and Artificial Intelligence to Track the Healing of Severe Burns.

Burn care management includes assessing the severity of burns accurately, especially distinguishing superficial partial-thickness burns from deep part...

Enhanced osteoporotic fracture prediction in postmenopausal women using Bayesian optimization of machine learning models with genetic risk score.

This study aimed to enhance the fracture risk prediction accuracy in major osteoporotic fractures (MOFs) and hip fractures (HFs) by integrating geneti...

Semi-supervised Learning for Generalizable Intracranial Hemorrhage Detection and Segmentation.

Purpose To develop and evaluate a semi-supervised learning model for intracranial hemorrhage detection and segmentation on an out-of-distribution head...

Estimation of racial and language disparities in pediatric emergency department triage using statistical modeling and natural language processing.

OBJECTIVES: The study aims to assess racial and language disparities in pediatric emergency department (ED) triage using analytical techniques and pro...

Using Machine Learning to Predict Unplanned Hospital Utilization and Chemotherapy Management From Patient-Reported Outcome Measures.

PURPOSE: Adverse effects of chemotherapy often require hospital admissions or treatment management. Identifying factors contributing to unplanned hosp...

A comprehensive exploration of artificial intelligence in orthopaedics within lower-middle-income countries: a narrative review.

Integrating Artificial Intelligence (AI) in orthopaedic within lower-middle-income countries (LMICs) promises landmark improvement in patient care. De...

Clinical applications of AI-prediction tools in spine surgery: a narrative review.

Spine surgery has grown into a wide, complex field encompassing trauma surgery to deformity to tumours. Artificial intelligence (AI) based technology ...

[Constructing a predictive model for the death risk of patients with septic shock based on supervised machine learning algorithms].

OBJECTIVE: To construct and validate the best predictive model for 28-day death risk in patients with septic shock based on different supervised machi...

Comparison of the problem-solving performance of ChatGPT-3.5, ChatGPT-4, Bing Chat, and Bard for the Korean emergency medicine board examination question bank.

Large language models (LLMs) have been deployed in diverse fields, and the potential for their application in medicine has been explored through numer...

RobOCTNet: Robotics and Deep Learning for Referable Posterior Segment Pathology Detection in an Emergency Department Population.

PURPOSE: To evaluate the diagnostic performance of a robotically aligned optical coherence tomography (RAOCT) system coupled with a deep learning mode...

Improved Vertebral Fracture Assessment: The Game-Changing Potential of Deep Learning with Multidetector CT.

APPLICATION OF ARTIFICIAL INTELLIGENCE IN CIVIL AND MILITARY MEDICINE.

Artificial intelligence (AI) encompasses the advancement of computers and robots, enabling them to surpass human capabilities in various aspects. By u...

Deep learning for acute rib fracture detection in CT data: a systematic review and meta-analysis.

OBJECTIVES: To review studies on deep learning (DL) models for classification, detection, and segmentation of rib fractures in CT data, to determine t...