Anesthesiology

Three pillars of artificial intelligence research in anesthesiology: welcoming address to the Korean Journal of Anesthesiology's new guidelines for machine learning and deep learning research.

Assessing bias in AI-driven psychiatric recommendations: A comparative cross-sectional study of chatbot-classified and CANMAT 2023 guideline for adjunctive therapy in difficult-to-treat depression.

The integration of chatbots into psychiatry introduces a novel approach to support clinical decision...

[New technologies serve as accelerators for breakthroughs in modern acupuncture research].

As one of China's most internationally influential original disciplines, acupuncture-moxibustion has...

Machine learning analysis of factors contributing to hypotension after lumbosacral epidural anaesthesia in dogs undergoing abdominal surgery.

The incidence of hypotension after a lumbosacral epidural in dogs depends on the volume of local ana...

Intracranial hemorrhage segmentation and classification framework in computer tomography images using deep learning techniques.

By helping the neurosurgeon create treatment strategies that increase the survival rate, automotive ...

An Integrated AI Cloud Sharing Framework for Predictive AI and Generative AI in Healthcare.

In 2019, Chi Mei Hospital built a private cloud AI service framework, incorporating HIS interface we...

Predicting Care Times at PACU.

Patients undergoing anesthetic surgery are treated postoperatively in a Post-Anesthesia Care Unit (P...

Current Trends and Future Directions in Lumbar Spine Surgery: A Review of Emerging Techniques and Evolving Management Paradigms.

: Lumbar spine surgery has undergone significant technological transformation in recent years, drive...

Analyzing Key Predictors of Postoperative Delirium Following Coronary Artery Bypass Grafting and Aortic Valve Replacement: A Machine Learning Perspective.

: Postoperative delirium (POD) is a frequent and severe complication following cardiac surgery, part...

Enhanced recovery programme in robotic hysterectomy.

The standard care for endometrial cancer includes total hysterectomy, bilateral salpingo-oophorectom...

Investigating perioperative pressure injuries and factors influencing them with imbalanced samples using a Synthetic Minority Over-sampling Technique.

This study investigates the use of machine learning (ML) models combined with a Synthetic Minority O...

Best practice in rheumatology new developments in ultrasound and MRI imaging of pediatric rheumatic diseases.

The evidence base for ultrasound and MRI imaging in pediatric rheumatic diseases continues to grow, ...

The effect of esketamine on perioperative anxiety and depressive symptoms in patients undergoing total hysterectomy.

AIM: This study aimed to evaluate the effect of esketamine on perioperative anxiety and depressive s...

Exploring Patient Experiences With and Perceptions of Robotic-Assisted Surgery in Denmark.

Although the use of robotic-assisted surgery (RAS) is increasing worldwide, qualitative research on ...

Concomitant Procedures, Black Race, Male Sex, and General Anesthesia Show Fair Predictive Value for Prolonged Rotator Cuff Repair Operative Time: Analysis of the National Quality Improvement Program Database Using Machine Learning.

PURPOSE: To develop machine learning models using the American College of Surgeons National Quality ...

Artificial intelligence-assisted approach to assessing bowel wall thickness in pediatric inflammatory bowel disease using intestinal ultrasound images.

BACKGROUND AND AIM: Intestinal ultrasound (IUS) potentially spares patients from repeated endoscopie...

Artificial Intelligence Literacy Levels of Perioperative Nurses: The Case of Türkiye.

Artificial intelligence (AI) experience among nurses in perioperative settings is crucial for effect...

Examining the frequency of artificial intelligence generated content in anesthesiology and intensive care journal publications: A cross sectional study.

The emergence of artificial intelligence (AI)-based linguistic models has revolutionized academic wr...

[From AI to polygenic risk scores: which innovations will shape the future of psychiatry?].

BACKGROUND: In recent years, developments have been made in various research domains, from treatment...

Just another tool in their repertoire: uncovering insights into public and patient perspectives on clinicians' use of machine learning in perioperative care.

OBJECTIVES: Successful implementation of machine learning-augmented clinical decision support system...

[Effect of an artificial intelligence-assisted recognition system on colonoscopy quality].

To explore the value of the artificial intelligence (AI)-assisted recognition system in the detecti...