Surgery

Expectations and Requirements of Surgical Staff for an AI-Supported Clinical Decision Support System for Older Patients: Qualitative Study.

BACKGROUND: Geriatric comanagement has been shown to improve outcomes of older surgical inpatients. ...

Spontaneous Hepatic Rupture Complicating Preeclampsia and HELLP Syndrome: A Case Report.

Spontaneous hepatic rupture is a rare complication that occurs in pregnant mothers with HELLP syndr...

Efficacy evaluation of a minimally invasive surgical procedure (oblique lateral interbody fusion) for lumbar spinal tuberculosis-retrospective cohort study.

OBJECTIVE: In the current study, to demonstrate the advantages of oblique lateral interbody fusion (...

Efficacy of preoperative prophylactic application of betamethasone on postoperative nausea and vomiting in patients undergoing total knee arthroplasty: a prospective randomized controlled trial.

BACKGROUND: The demand for total knee arthroplasty (TKA) is increasing, yet postoperative nausea and...

Pixels to precision: Neuroradiology's leap into 3D printing for personalized medicine.

The realm of precision medicine, particularly its application within various sectors, shines notably...

Biochemical, Radiographic, or Pathologic Response to Neoadjuvant Chemotherapy in Resected Pancreatic Cancer: Which Is Best?

OBJECTIVE: To examine the optimal method of assessing response to neoadjuvant therapy (NAT) in patie...

Development of a machine learning model for prediction of intraventricular hemorrhage in premature neonates.

PURPOSE: Intraventricular hemorrhage (IVH) is a common and severe complication in premature neonates...

Machine learning-based predictive models for perioperative major adverse cardiovascular events in patients with stable coronary artery disease undergoing noncardiac surgery.

BACKGROUND AND OBJECTIVE: Accurate prediction of perioperative major adverse cardiovascular events (...

Deep learning-assistance significantly increases the detection sensitivity of neurosurgery residents for intracranial aneurysms in subarachnoid hemorrhage.

OBJECTIVE: The purpose of this study was to evaluate the effectiveness of a deep learning model (DLM...

A clinical practical model for preoperative prediction of visual outcome for pituitary adenoma patients in a retrospective and prospective study.

OBJECTIVE: Preoperative prediction of visual recovery after pituitary adenoma resection surgery rema...

Prediction of postoperative stroke in patients experienced coronary artery bypass grafting surgery: a machine learning approach.

BACKGROUND: Coronary artery bypass grafting (CABG) surgery has been a widely accepted method for tre...

Smartphone pupillometry with machine learning differentiates ischemic from hemorrhagic stroke: A pilot study.

OBJECTIVES: Similarities between acute ischemic and hemorrhagic stroke make diagnosis and triage cha...

Machine learning and deep learning algorithms in stroke medicine: a systematic review of hemorrhagic transformation prediction models.

BACKGROUND: Acute ischemic stroke (AIS) is a major cause of morbidity and mortality, with hemorrhagi...

Systematic evaluation of machine learning models for postoperative surgical site infection prediction.

BACKGROUND: Surgical site infections (SSIs) lead to increased mortality and morbidity, as well as in...

Artificial intelligence in surgical pathology - Where do we stand, where do we go?

Surgical and neuropathologists continuously search for new and disease-specific features, such as in...

Stress testing deep learning models for prostate cancer detection on biopsies and surgical specimens.

The presence, location, and extent of prostate cancer is assessed by pathologists using H&E-stained ...

Imaging-guided bioresorbable acoustic hydrogel microrobots.

Micro- and nanorobots excel in navigating the intricate and often inaccessible areas of the human bo...

Acupuncture and moxibustion as adjunctive therapy for postoperative gastrointestinal dysfunction in gastric cancer: a systematic review and network meta-analysis.

OBJECTIVES: This study aimed to evaluate and compare the efficacy and safety of different acupunctur...

Editorial: The evolution of minimally invasive urologic surgery: innovations, challenges, and opportunities.

Development and validation of interpretable machine learning models for postoperative pneumonia prediction.

BACKGROUND: Postoperative pneumonia, a prevalent form of hospital-acquired pneumonia, poses signific...

Machine Learning-Based Prediction for In-Hospital Mortality After Acute Intracerebral Hemorrhage Using Real-World Clinical and Image Data.

BACKGROUND: Machine learning (ML) techniques are widely employed across various domains to achieve a...