Surgery

Quality of AI-generated post-operative patient education after minimally invasive gynecologic surgery: A comparative analysis.

STUDY OBJECTIVE: To compare the quality of AI-generated responses to gynecologic post-operative questions with educational materials published by professional societies. DESIGN: Comparative analysis of published and AI-generated patient education relating to hysterectomy, hysteroscopy, laparoscopy, and management of conditions such as endometriosis and abnormal uterine bleeding. SETTING: Questions...

EEG monitoring in the operating room: current uses and perspectives - a narrative review.

CONTEXT AND IMPORTANCE: With over 300 million surgeries performed under general anaesthesia annually, optimising perioperative brain health has become a critical public health priority. Electroencephalogram (EEG) monitoring, initially conceived to prevent awareness during anaesthesia, is now emerging as a tool for assessing cognitive vulnerability and predicting neurocognitive outcomes. OBJECTIVES...

Does lens opacity matter? The effect of cataract on deep learning based cardiovascular disease risk scores from fundus photos.

PURPOSE: To investigate the effect of cataracts on a deep learning (DL) model for cardiovascular disease (CVD) risk prediction. METHODS: This retrospe...

Machine learning-based MRI radiomics identifies patients with degenerative cervical myelopathy and predicts baseline function.

PURPOSE: The diagnosis of Degenerative cervical myelopathy (DCM) relies on clinical evaluation and conventional MRI, yet early symptoms are subtle and...

Technical challenges in autonomous robotic ultrasound examinations: perception, planning, and control.

Ultrasound is one of the most widely used medical imaging modalities in clinical practice. Robot-assisted ultrasound systems (RAUS) offer significant ...

Beyond Broca and Wernicke: Epilepsy surgery in the language areas.

Epilepsy surgery in language areas is challenged by the intricacies of presurgical workup and surgical planning. In recent decades, the view of langua...

Integrating handcrafted and deep learning MRI signatures: an interpretable framework for predicting chemotherapy benefit in glioma.

The molecular and spatial heterogeneity of gliomas severely limits accurate prediction of postoperative adjuvant chemotherapy efficacy, representing a...

Electronic health record-derived machine learning model for hypoglycemia risk prediction in type 2 diabetes mellitus patients: development and validation.

BACKGROUND: Hypoglycemia is a serious complication of diabetes. Early recognition of hypoglycemia can improve clinical prognosis, however, traditional...

Development and external validation of multiple machine learning-based models for breast cancer-specific survival prediction in postoperative patients with invasive breast cancer: a study based on the SEER database and an external cohort.

BACKGROUND: Patients with invasive breast cancer (IBC) account for the vast majority of breast cancer cases and exhibit significant heterogeneity; hen...

Machine learning prediction of long-term postoperative pneumonia risk: a retrospective cohort study.

BACKGROUND: Postoperative pneumonia is a significant complication, highlighting a patient's ongoing vulnerability. While traditional tools focus on sh...

AI-assisted preoperative planning improves component sizing accuracy in Oxford unicompartmental knee arthroplasty: a retrospective cohort study with 24-month follow-up.

BACKGROUND: Accurate implant sizing is critical for clinical outcomes in Oxford unicompartmental knee arthroplasty (UKA), yet reliable preoperative pl...

Relationship between ileocolic arterial stump length and lymph node yield - a retrospective study using machine learning.

PURPOSE: In right-sided colon cancer surgery, ileocolic artery stump length may reflect the extent of mesenteric resection and lymph node harvest. Thi...

Robotic Technologies for Hand Recovery After Stroke: A Reflection on Research Paths in Honor of Dr. Steven Wolf.

Over the past 35 years, my work has focused on developing and studying robotic technologies to promote hand and arm recovery after stroke. In this Poi...

Association between the development of sepsis and the BAR index in patients with acute pancreatitis: A retrospective investigation based on MIMIC-IV database.

Sepsis, as a severe complication of acute pancreatitis (AP), needs to be identified and treated as early as possible. The blood urea nitrogen-to-album...

Common biomarkers of Alzheimer disease and postoperative delirium.

Alzheimer disease (AD) and Postoperative delirium (POD) may share a common mechanism, but their shared genes and potential novel therapeutic targets r...

Ultrasound-Mediated Thrombolysis: From Mechanistic Insights to Advanced Nanoplatforms and Clinical Translation.

Although pharmacological thrombolysis and mechanical thrombectomy are standard treatments for thromboembolic diseases, they are limited by hemorrhagic...

Machine Learning-Based Prediction of Treatment Success, Postoperative Pain, and Analgesic Use After Full Pulpotomy in Permanent Molars with Symptomatic Irreversible Pulpitis.

INTRODUCTION: This study aimed to develop and evaluate machine learning (ML) models for predicting treatment success, postoperative pain, and analgesi...

Deep Learning-Based Diagnosis of Parotid Gland Tumors on CT Images: A Multi-view Approach for Preoperative Differentiation of Benign and Malignant Lesions.

BACKGROUND: Accurate preoperative differentiation between benign and malignant parotid gland tumors is essential for guiding surgical planning and tre...

Does Patient History Influence Capsular Contracture? An Exploratory Analysis with Machine Learning.

BACKGROUND: Capsular contracture (CC) is a frequent and distressing complication of breast augmentation and reconstruction. Although numerous patient-...

M-Tune: imbalanced data handling in machine learning by tuning the decision threshold.

Overprediction of the majority class and poor predictive performance are the major issues when training machine learning classifiers with imbalanced d...