Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1192/bjp.111.481.1226-a | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
A Novel Artificial Intelligence-Enhanced Digital Network for Prehospital Emergency Support: Community Intervention Study.
J Med Internet Res
January 2025
Department of Cardiology, Yonsei University College of Medicine, Seoul, Republic of Korea.
Background: Efficient emergency patient transport systems, which are crucial for delivering timely medical care to individuals in critical situations, face certain challenges. To address this, CONNECT-AI (CONnected Network for EMS Comprehensive Technical-Support using Artificial Intelligence), a novel digital platform, was introduced. This artificial intelligence (AI)-based network provides comprehensive technical support for the real-time sharing of medical information at the prehospital stage.
View Article and Find Full Text PDFSign Language Recognition System for Deaf Patients: Protocol for a Systematic Review.
JMIR Res Protoc
January 2025
Department of Computer Science, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.
Background: Individuals with hearing impairments may face hindrances in health care assistance, which may significantly impact the prognosis and the incidence of complications and iatrogenic events. Therefore, the development of automatic communication systems to assist the interaction between this population and health care workers is paramount.
Objective: This study aims to systematically review the evidence on communication systems using human-computer interaction techniques developed for deaf people who communicate through sign language that are already in use or proposed for use in health care contexts and have been tested with human users or videos of human users.
Updates on CAD risk assessment: using the coronary artery calcium score in combination with traditional risk factors.
Egypt Heart J
January 2025
Rajaie Cardiovascular, Medical and Research Institute, Valiasr Ave, Hashemi Rafsanjani (Niayesh) Intersection, Tehran, Iran.
Background: Coronary artery disease (CAD) is the third leading cause of death worldwide, so prevention and early diagnosis play important roles to reduce mortality and morbidity. Traditional risk-score assessments were used to find the at-risk patients in order to prevent or early treatment of CAD. Adding imaging data to traditional risk-score systems will able us to find these patients more confidently and reduce the probable mismanagements.
View Article and Find Full Text PDFWho is a candidate at the initial presentation? Prediction of positive lateral lymph node and survival after dissection.
Tech Coloproctol
January 2025
Department of Colorectal Surgery, College of Medicine, Seoul St. Mary's Hospital, The Catholic University of Korea, 222 Banpodearo, Seochogu, Seoul, 06591, Korea.
Metastatic lateral pelvic lymph node (LPN) in rectal cancer has a significant clinical impact on the prognosis and treatment strategies. But there are still debates regarding prediction of lateral pelvic lymph node metastasis and its oncological impact. This review explores the evidence for predicting lateral pelvic lymph node metastasis and survival in locally advanced rectal cancer.
View Article and Find Full Text PDFA Review of Leveraging Artificial Intelligence to Predict Persistent Postoperative Opioid Use and Opioid Use Disorder and its Ethical Considerations.
Curr Pain Headache Rep
January 2025
Division of Perioperative Informatics, Department of Anesthesiology, University of California, San Diego, La Jolla, CA, USA.
Purpose Of Review: Artificial intelligence (AI) offers a new frontier for aiding in the management of both acute and chronic pain, which may potentially transform opioid prescribing practices and addiction prevention strategies. In this review paper, not only do we discuss some of the current literature around predicting various opioid-related outcomes, but we also briefly point out the next steps to improve trustworthiness of these AI models prior to real-time use in clinical workflow.
Recent Findings: Machine learning-based predictive models for identifying risk for persistent postoperative opioid use have been reported for spine surgery, knee arthroplasty, hip arthroplasty, arthroscopic joint surgery, outpatient surgery, and mixed surgical populations.
Want AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!