Surgery

Performance of large language models in a high-stakes dental assessment: evidence from the Turkish dentistry specialization examination.

Large language models (LLMs) are increasingly used in dental education; however, their performance on high-stakes national examinations remains insufficiently explored. The Dentistry Specialization Examination (DUS) in Türkiye is a standardized gateway to postgraduate dental training and includes a dedicated periodontology component. No previous study has evaluated contemporary LLM accuracy on DUS...

A Multimodal, Multitask Prediction Framework for Diagnosis and Prognosis of Clear Cell Renal Cell Carcinoma.

The purpose of this study is to develop and validate a multimodal, multitask prediction framework for clear cell renal cell carcinoma (ccRCC) by integrating preoperative CT radiomics, pathology-derived biomarker data from preoperative biopsy specimens, and clinical variables. The model was built for pathologically confirmed ccRCC and excluded other RCC histologic subtypes (e.g., papillary and chro...

Feasibility of using artificial intelligence models to identify the obturator nerve in laparoscopic selective lateral pelvic lymph node dissection.

BACKGROUND: Protecting the obturator nerve (ON) is crucial during selective lateral pelvic lymph node dissection (SLPLND). This study evaluated the fe...

Optimizing the mathematical model and technical standards for unilateral biportal endoscopic spinal surgery through machine learning-based video analysis.

OBJECTIVE: To enhance the efficacy of the unilateral biportal endoscopic spinal procedure, the spinal triangle concept is proposed, integrating a digi...

Evaluation of Machine Learning and Statistical Models for Predicting Long Term Gastrostomy Tube Dependency in Patients Undergoing Major Oral Cavity Cancer Surgery With Free Flap Reconstruction.

BACKGROUND: Swallowing dysfunction and long-term gastrostomy tube dependence are common morbidities after oral cavity cancer resection with free flap ...

Reframing Response in Neoadjuvant Chemotherapy for Ovarian Cancer: Integrating Molecular and Functional Biomarkers.

BACKGROUND: Neoadjuvant chemotherapy (NACT) is an established treatment strategy for advanced epithelial ovarian cancer, particularly for patients wit...

Prediction of Exercise Intolerance in the Recovery Period After Cardiovascular Surgery Using Perioperative Clinical Parameters.

OBJECTIVE: To develop and validate a machine learning model for predicting reduced exercise capacity at 3 months postoperatively using clinical parame...

Development and validation of interpretable machine learning models to predict 30-day mortality in patients with intracerebral hemorrhage.

Intracerebral hemorrhage (ICH) carries high early mortality. To enable personalized decision-making, we developed and validated interpretable machine ...

Predicting and identifying determinants of stunting among school-aged children in Ethiopia: a machine learning approach.

BACKGROUND: Childhood stunting remains a major public health concern, reflecting chronic undernutrition and long-term socioeconomic disadvantage. Amon...

A systematic approach to standardizing the visual appearance of endometriotic lesions for artificial intelligence recognition.

INTRODUCTION: Numerous studies have shown that the diagnostic performance and reproducibility of visual recognition of endometriosis during laparoscop...

Deep learning-based multimodal fusion of vibrational spectroscopy and clinical data for aortic dissection diagnosis and prognosis.

BACKGROUND: Aortic dissection and myocardial infarction are two life-threatening acute cardiovascular conditions with similar clinical presentations b...

AI in predicting the macrotrabecular-massive subtype of HCC and informing treatment selection: a multi-center and prospective validation study.

The macrotrabecular-massive (MTM) subtype of hepatocellular carcinoma (HCC) is associated with aggressive biology and poor prognosis. We aimed to deve...

Topological imaging of single-cell CAF heterogeneity for predicting prognosis and adjuvant chemotherapy benefit in pancreatic cancer.

PURPOSE: Cancer-associated fibroblasts (CAFs) are central drivers of PDAC progression and therapeutic resistance, yet their preoperative clinical util...

Automated surgical phase recognition and analysis in single-incision laparoscopic cholecystectomy using artificial intelligence.

BACKGROUND: Single-incision laparoscopic cholecystectomy (SILC) is technically more challenging and has a steeper learning curve compared to conventio...

Machine learning prediction of local control after Gamma Knife radiosurgery to post-resection cavities from brain metastases: a proof-of-concept study.

BACKGROUND: Large symptomatic brain metastases require initial surgical resection. However, local control (LC) after Gamma Knife radiosurgery (GKRS) t...

Predicting antenatal care dropout using machine learning and describing maternal and neonatal outcomes by dropout status in Sidama Region, Ethiopia: a retrospective cohort study.

OBJECTIVES: We aimed to develop and validate machine-learning models to predict antenatal care (ANC) dropout and describe maternal and neonatal outcom...

Identification of therapeutic targets and postoperative recurrence prediction model construction for hepatocellular carcinoma based on systematic mendelian randomization.

BACKGROUND AND STUDY AIMS: Hepatocellular carcinoma (HCC) has a high risk of postoperative recurrence. This study aimed to develop a transcriptome-bas...

Serum Proteomic Profiling Implicates a Dysregulated Neurohormonal-Inflammatory Axis in Post-Fontan Sinus Tachycardia.

BACKGROUND: Postoperative sinus tachycardia is a poorly understood complication following the Fontan procedure. The molecular signaling cascades trigg...

Artificial intelligence for detection, prediction, and severity classification of diabetic peripheral neuropathy: a systematic review.

BACKGROUND: Diabetic peripheral neuropathy (DPN) is a common complication of diabetes and an important contributor to foot ulceration and lower limb a...

Evaluating AI in postoperative rehabilitation of axillary web syndrome after breast cancer surgery: ChatGPT vs DeepSeek.

OBJECTIVE: To systematically compare two generative artificial intelligence (AI) models, ChatGPT and DeepSeek in the rehabilitation management for axi...