Surgery

Ethical Considerations for the Use of Artificial Intelligence Tools in Surgery.

Artificial intelligence (AI) is rapidly transforming surgical care, offering unprecedented capabilities in diagnostics, planning, and intraoperative guidance. However, its integration into clinical practice raises complex ethical challenges that must be addressed to ensure responsible and equitable use. This chapter aims to explore the ethical implications of AI in surgery through the lens of the ...

From Algorithm to Operatory: How Reliable Is Artificial Intelligence in Educating Patients on External Sinus Lifting?

BACKGROUND: Large language models (LLMs) such as Chat Generative Pre-Trained Transformer (ChatGPT; OpenAI, San Francisco, CA) and Claude (Anthropic, San Francisco, CA) are increasingly used by patients seeking information about surgical procedures, including external sinus lifting. However, the accuracy, quality, and readability of these artificial intelligence (AI)-generated explanations remain u...

Artificial Intelligence as the Ultimate Operative Assistant.

Artificial intelligence (AI) is poised to become transformational in many aspects of modern society and has attracted significant interest within the ...

Artificial Intelligence to Improve Patient-Physician Communication in Surgery.

Effective patient-physician communication is a cornerstone of surgical care, yet increasing clinical complexity and time constraints often limit oppor...

Impact of continuing renin-angiotensin-aldosterone system inhibitors before surgery on intraoperative hypotensive events: a secondary analysis of the STOP-or-NOT Trial.

BACKGROUND: The multicentre STOP-or-NOT trial has shown that continuation of renin-angiotensin-aldosterone inhibitors (RAASis) before major noncardiac...

Automatic measurement and evaluation of anterior segment anatomical structures via UBM images using a deep learning-based approach.

PURPOSE: To develop a deep-learning model capable of measuring essential anterior segment (AS) parameters derived from preoperative ultrasound biomicr...

Comparison of blood sample quality and test results between robotic and manual venipuncture: a pilot study.

OBJECTIVES: This study aimed to evaluate the feasibility of robotic venipuncture in clinical settings and compare its performance with manual venipunc...

Predictors of Outcome Clusters in Patients With Unruptured Intracranial Aneurysms Treated With Microsurgery: An Unsupervised Machine Learning Analysis.

BACKGROUND AND OBJECTIVES: Identifying surgical candidates who are prone to poor outcomes is crucial for adapting treatment and ensuring optimal outco...

Machine learning models for predicting postoperative complications following mandibular third molar surgery: Development, validation, and explainable AI insights.

The surgical removal of impacted mandibular third molars is a routine procedure in oral and maxillofacial surgery but is consistently associated with ...

Outcome Assessment in Stroke Using Multiparametric MRI: Integrating Infarct Location, Radiomics, and Global Brain Frailty.

BACKGROUND: Accurate assessment of 90-day functional outcomes after anterior circulation large vessel occlusion (LVO) stroke remains challenging. Conv...

[When everything is well-coordinated in an interdisciplinary manner-Is there a need for operating room management?].

Even in the ideal case of well-coordinated cooperation between anesthesiological and surgical as well as interventional colleagues, a departmental con...

Building a national repository of dural-based lesions: clinical, pathological, and demographic insights from the Indian population.

BACKGROUND: Meningiomas are the most common dural-based intracranial tumors, yet Indian literature is predominantly composed of limited single-center ...

Are we ready for amyloid-related imaging abnormalities (ARIA) monitoring? A European survey among neuroradiologists and neurologists by the ESNR/EAN Working Group.

OBJECTIVES: Amyloid-lowering immunotherapies can cause amyloid-related imaging abnormalities (ARIA), requiring brain MRI for detection and monitoring....

Can Large Language Models Be a Viable Tool for Consensus Working Groups? Experience of the Ventral Rectopexy Expert Consensus Group.

BACKGROUND: The Ventral Rectopexy International Expert Panel recently published a consensus update on ventral rectopexy. The ability of large language...

A Summary of Artificial Intelligence in Gynecologic Surgery.

Artificial intelligence is transforming healthcare, including obstetrics and gynecology, with applications for diagnostics, outcome prediction, and cl...

AI at the Helm: Evaluating Claude 3.5 Sonet and ChatGPT-4.0 in Tympanoplasty Management.

BACKGROUND: Artificial intelligence (AI) is increasingly being integrated into health care, offering new possibilities for postoperative management. L...

Minimally Invasive, Label-Free, Point-of-Care Histopathological Diagnostic Platform of Malignant Tumors of the Female Reproductive System Based on Raman Spectroscopy and Machine Learning.

Fast intraoperative histopathology is critical for optimal surgery in ovarian, endometrial and cervical cancers, yet frozen-section pathology is slow ...

Deep Learning for Ultrasound-Based Auxiliary Diagnosis of Emergency Ascites.

OBJECTIVE: The Focused Assessment with Sonography for Trauma (FAST) enables rapid detection of free intraperitoneal fluid, facilitating timely managem...

A machine learning-driven app for predicting the need for post-operative respiratory support in liver transplant recipients.

BACKGROUNDS: Liver transplantation (LT) is a life-saving procedure for patients with end-stage liver disease, yet post-operative complications, partic...

The role of artificial intelligence in estimating stroke events in Moyamoya patients: A systematic review and meta-analysis of diagnostic test accuracy.

INTRODUCTION: Moyamoya disease (MMD) and syndrome (MMS) are rare cerebrovascular arteriopathies marked by progressive internal carotid stenosis, fragi...