Surgery

Development and validation of a generalisable machine learning algorithm for identifying interstitial lung disease cohorts: a retrospective cohort study.

BACKGROUND: Large electronic databases are powerful tools for studying rare diseases, however accurate Interstitial Lung Disease (ILD) classification remains challenging. Rule-based approaches rely heavily on diagnostic codes-unreliable markers of ILD. We aimed to develop and externally validate an ILD classification algorithm that robustly identifies prevalent cases using routinely captured elect...

Performance of AI vs radiology residents in the detection of intracranial hemorrhage on emergency CT: a real-world analysis.

OBJECTIVE: To evaluate the performance of a commercial artificial intelligence (AI) software in detecting intracranial hemorrhage (ICH) in emergency settings, compared to on-call radiology residents. MATERIALS AND METHODS: All consecutive unenhanced cerebral CT-scans performed in a single center over a 3-month period in the emergency department in patients with suspected ICH, initially interpreted...

Prediction of Postoperative Pancreatic Fistula Occurrence by the Pancreatic Stump Shape and Remnant Pancreatic Volume Measured Using AI-Guided Three-Dimensional Simulation.

BACKGROUND: When three-dimensional computer graphics (3DCG) images are used, artificial intelligence (AI) engines can semiautomatically estimate the p...

Unraveling the role of polyamine metabolism in postoperative delirium: insights into biochemical mechanisms and biomarker potential.

Postoperative delirium (POD) is a common complication in older surgical patients, linked to long-term cognitive decline and progression to dementia, y...

Clinical-imaging model for predicting prognosis in contemporary endodontic microsurgery: a retrospective machine learning-based study.

INTRODUCTION: Predictive tools for endodontic microsurgery (EMS) outcomes remain limited. This study evaluated the performance of various machine lear...

Multidimensional analysis of postoperative nursing challenges in oral cancer surgery: a retrospective study of 245 patients and proposal of the PROTECT mode.

PURPOSE: The quality of postoperative care for oral tumors critically influences patient prognosis and quality of life; however, current nursing syste...

Multimodal CT for Predicting Microvascular Invasion in Solitary cHCC-CCA: Dual-Center External Validation.

RATIONALE AND OBJECTIVES: Preoperative prediction of microvascular invasion (MVI) in combined hepatocellular-cholangiocarcinoma (cHCC-CCA) remains dif...

Multiparametric MRI-Based Deep Learning and Radiomics for Predicting Progression-Free Survival Benefit in Patients with Hepatocellular Carcinoma Treated with Immunotherapy and Targeted Therapy Plus Transarterial Chemoembolization: A Bicentric Study.

RATIONALE AND OBJECTIVES: The non-invasive biomarkers for predicting progression-free survival (PFS) in patients with hepatocellular carcinoma (HCC) t...

AI in epilepsy neuroimaging.

PURPOSE OF REVIEW: Recent advances in the capabilities and usability of artificial intelligence (AI) architectures coupled with increased availability...

Inflammatory indices, machine learning and artificial intelligence in tubal ectopic pregnancy management.

OBJECTIVE: To assess the predictive value of hematologic and biochemical inflammatory indices for methotrexate (MTX) treatment outcomes in tubal ectop...

Preoperative prediction of preserved renal parenchymal volume via multilevel CT feature fusion: a proof-of-concept study.

PURPOSE: Accurate preoperative prediction of preserved renal parenchymal volume (RPV) following partial nephrectomy (PN) is critical for individualize...

Topologically distinct 2D and 3D intratumoral heterogeneity scores for preoperatively predicting invasiveness in stage I lung adenocarcinoma: A multicenter study.

This multicenter study aims to enhance the preoperative prediction of pathological invasiveness in clinical stage I lung adenocarcinoma (LUAD) by deve...

Multi-branch convolutional neural network and intracranial EEG high-frequency oscillations predict post-surgical seizure outcomes.

OBJECTIVE: Pathological High-Frequency Oscillations (HFOs) identify epileptogenic cortex, but their surgical utility is unproven. Current epilepsy sur...

AI-Augmented Mixed Reality for 3D Visualization of Perforator Vessels: A Feasibility Study in Fibular Flap Surgery.

OBJECTIVE: Using the fibular flap as a model, this study aims to develop a three-dimensional visualization method for perforator vessels. This method ...

Flow rate determination in a two-phase system using radioactive particle tracking and deep learning.

In the oil industry, accurate flow rate determination and control in pipelines are critical for ensuring operational efficiency. However, most convent...

Predicting Surgical Outcomes in Breast Reconstruction With Machine Learning: A Systematic Review.

INTRODUCTION: The applications of artificial intelligence (AI) in plastic surgery have grown considerably in recent years. As large patient datasets b...

Predicting surgical intensive care unit readmission with machine learning model: Bi-center training and validation.

BACKGROUND: Patients readmitted to the surgical intensive care unit (SICU) face a high risk of mortality and increased hospital costs. Identifying pat...

Neoadjuvant Radiation is Causally Linked to Increased Operative Time and Perioperative Blood Transfusion in Pancreatic Ductal Adenocarcinoma.

INTRODUCTION: Blood transfusion in patients undergoing surgical resection for pancreatic ductal adenocarcinoma (PDAC) is associated with worse outcome...

Strategies to reduce perioperative acute kidney injury in non-cardiac adult surgeries: the secret sauce.

Acute kidney injury is a common perioperative complication that leads to significant downstream effects on the patient and the health system. Patients...

Machine Learning for Predicting Stroke Risk Stratification Using Multiomics Data: Systematic Review.

BACKGROUND: Stroke is a complex, multidimensional disorder influenced by interacting inflammatory, immune, coagulation, endothelial, and metabolic pat...