Surgery

Deep learning models for predicting opaque bubble layer morphology of keratorefractive lenticule extraction before laser scanning.

PURPOSES: To develop deep learning (DL) models for predicting opaque bubble layer (OBL) morphology and area before femtosecond laser scanning in keratorefractive lenticule extraction (KLEx) procedures. METHODS: A total of 10276 frames from 5138 KLEx surgical videos, involving 2698 patients, were used to construct and validate the DL models. Suction-initiated frames captured before laser scanning w...

Artificial Intelligence-Assisted Point-of-Care Ultrasound for Evaluating Left Ventricular Ejection Fraction: A Systematic Review of Prospective Observational Studies.

Artificial intelligence (AI) embedded in point-of-care ultrasound (POCUS) could reduce operator dependence in left ventricular ejection fraction (LVEF) assessment and accelerate bedside decision making by non-cardiologists and non-radiologists. Prospective comparative studies evaluating real-time AI-assisted POCUS for LVEF across point-of-care settings were systematically reviewed. The PubMed/MEDL...

Predictive artificial intelligence in maxillofacial surgery: a systematic review.

The objective of this systematic review is to outline the current landscape and applications of predictive artificial intelligence (AI) in maxillofaci...

Artificial intelligence-enhanced ECG score for perioperative risk assessment in non-cardiac surgery.

AIMS: The role of electrocardiography (ECG) has been limited in the preoperative risk evaluation in noncardiac surgery due to its low prognostic value...

How threshold customisation affects the performance of a multiclass X-ray AI model for primary care triage: a retrospective study.

OBJECTIVES: To describe the structured process of threshold optimisation for a commercially available multiclass chest X-ray (CXR) deep learning model...

Towards real time AI-augmented fluorescence-guided surgery: Evidence and translational readiness across neurosurgical, gynaecological, and thoracic oncology.

Fluorescence-guided surgery (FgS) is increasingly used across oncologic specialties to enhance intraoperative visualisation of tumour tissue and lymph...

Multimodal brain-gut-sleep phenotypes predict delirium, long-term cognitive decline, and survival after colorectal cancer surgery.

BACKGROUND: Neuroimmune, circadian, autonomic, and gut-brain processes jointly shape vulnerability to postoperative delirium and long-term cognitive d...

Research on the Application Value of Blood Plasma Autofluorescence Spectroscopy Model Constructed by Machine Learning Algorithms in Identifying the Types of Post-operative Kidney Transplantation Injury.

BACKGROUND: This study aimed to assess the value of blood plasma autofluorescence spectroscopy in classifying renal injury after renal transplantation...

Spatiotemporal Remodeling of Bone as a Reversibly Adaptive Biological Material in Djungarian Hamsters under Regulated Photoperiod Conditions.

Bone loss in humans is typically progressive and difficult to reverse, posing challenges for both pharmacological therapy and the long-term performanc...

Predicting Persistent Renal Failure Necessitating Dialysis in Patients Undergoing Elective, Open Thoracoabdominal Aortic Aneurysm Repair.

BACKGROUND: Acute renal failure remains a significant complication after open thoracoabdominal aortic aneurysm (TAAA) repair and is associated with hi...

The application of Machine learning in predicting the outcomes of minimally invasive treatments for uterine Fibroids: A systematic review and meta-analysis.

RATIONALE AND OBJECTIVES: Uterine fibroids (UFs) are common benign tumors that impact women's health, particularly through symptoms such as abnormal b...

Deep Learning and Machine Learning for Differentiation Between Contrast Extravasation and Hemorrhagic Transformation in Post-Thrombectomy Stroke CT.

BACKGROUND: Mechanical thrombectomy (MT) improves outcomes in acute ischemic stroke (AIS) but often results in hyperdensities on non-contrast CT (NCCT...

Development and validation of a machine learning model for prediction of 1-year mortality following ST-elevation myocardial infarction: a retrospective cohort study.

OBJECTIVES: To develop a machine learning (ML)-based risk prediction model for 1-year mortality in ST-elevation myocardial infarction (STEMI) patients...

Effect of caudal fin shape on swimming performance of a flying fish robot.

The advancement of robotic fish necessitates examination of whether caudal fins should be specifically designed for individual body shapes or if gener...

Outcomes of Artificial Intelligence Enhanced Colonoscopy in a Tertiary Clinical Setting.

BACKGROUND AND AIMS: Colonoscopies reduce colorectal cancer incidence and mortality, but challenges remain in detecting all precancerous lesions. Oper...

Global research trends in robotic-assisted thoracoscopic surgery: a multidimensional analysis from 2000 to 2025.

OBJECTIVE: Robotic-assisted thoracoscopic surgery (RATS) has transformed thoracic surgery, yet fragmented research patterns obscure critical developme...

Explainable machine learning model based on clinical and radiological features for predicting hematoma expansion or rebleeding after decompressive craniectomy in traumatic brain injury: a bicentric cohort study.

BACKGROUND: Hematoma expansion or rebleeding after decompressive craniectomy (DC) is a critical determinant of poor prognosis in traumatic brain injur...

Clinical Applications of Data Science and Machine Learning in the Pediatric Cardiac Intensive Care Unit.

To synthesize and critically appraise applications of machine learning (ML) in pediatric cardiac intensive care, focusing on algorithm performance, va...

Development and evaluation of a prediction model for adult ICU hemorrhage using only continuous cardiorespiratory data.

Develop and evaluate whether a model trained to detect the physiological signature of hemorrhage in ICU patients generalizes to other cohorts. App...

[Application of a novel robot-assisted navigation system in CT-guided percutaneous lung biopsy].

Objective: To compare the clinical efficacy and safety of robot-assisted navigation systems with those of the conventional puncture localization metho...