Surgery

Robot-Assisted Laparoscopic Hysterectomy with Artificial Intelligence-Analyzed Imaging: Robot-Assisted Laparoscopic Hysterectomy with AI Imaging.

Development and validation of a cardiac surgery-associated acute kidney injury prediction model using the MIMIC-IV database.

OBJECTIVE: This study aimed to develop an innovative early prediction model for acute kidney injury (AKI) following cardiac surgery in intensive care unit (ICU) settings, leveraging preoperative and postoperative clinical variables, and to identify key risk factors associated with AKI.

Deep learning neural network prediction of postoperative complications in patients undergoing laparoscopic right hemicolectomy with or without CME and CVL for colon cancer: insights from SICE (Società Italiana di Chirurgia Endoscopica) CoDIG data.

BACKGROUND: Postoperative complications in colorectal surgery can significantly impact patient outcomes and healthcare costs. Accurate prediction of t...

Extremity Soft Tissue Sarcoma Reconstruction Nomograms: A Clinicoradiomic, Machine Learning-Powered Predictor of Postoperative Outcomes.

PURPOSE: The choice of wound closure modality after limb-sparing extremity soft-tissue sarcoma (eSTS) resection is fraught with uncertainty. Leveragin...

Surgery for Lumbar Disc Herniation: Surgeon's Clinical Judgment Versus Actual Improvement in Patient Reported Outcomes.

Study DesignLongitudinal Cohort.ObjectivesTo determine if a surgeon's clinical judgment can predict clinical outcomes after surgery for LDH.MethodsSur...

Exploring Machine Learning Models for Vault Safety in ICL Implantation: A Comparative Analysis of Regression and Classification Models.

INTRODUCTION: Accurate prediction of postoperative vault height following implantable collamer lens (ICL) V4c implantation is critical for minimizing ...

Evaluation of artificial-intelligence-based liver segmentation and its application for longitudinal liver volume measurement.

BACKGROUND: Accurate liver-volume measurements from CT scans are essential for treatment planning, particularly in liver resection cases, to avoid pos...

Robotic Central Pancreatectomy with Omental Pedicle Flap: Tactics and Tips.

BACKGROUND: Robotic central pancreatectomy is increasingly used for pre- or low-grade malignant tumors in the pancreatic body balancing preservation o...

Thalamic neural activity and epileptic network analysis using stereoelectroencephalography: a prospective study protocol.

INTRODUCTION: Epilepsy is a prevalent chronic neurological disorder, with approximately one-third of patients experiencing intractable epilepsy, often...

A Machine Learning Model to Predict Treatment Effect Associated with Targeted Temperature Management After Cardiac Arrest.

BACKGROUND: Targeted temperature management (TTM) has been associated with neurological recovery among comatose survivors of cardiac arrest. The aim o...

Artificial Intelligence for Head and Neck Squamous Cell Carcinoma: From Diagnosis to Treatment.

Head and neck squamous cell carcinoma (HNSCC) remains a globally prevalent malignancy with high morbidity and mortality. Despite therapeutic advances,...

Machine learning method based on radiomics help differentiate posterior pituitary tumors from pituitary neuroendocrine tumors and craniopharyngioma.

Posterior pituitary tumors (PPTs) are rare neoplasms, but easily misdiagnosed as pituitary neuroendocrine tumor (PitNET) and craniopharyngioma. This s...

High-Dimensional Operator Learning for Molecular Density Functional Theory.

Classical density functional theory (cDFT) provides a systematic framework to predict the structure and thermodynamic properties of chemical systems t...

Comparison of responses from different artificial intelligence-powered chatbots regarding the All-on-four dental implant concept.

BACKGROUND: Recent advancements in Artificial Intelligence (AI) have transformed the healthcare field, particularly through chatbots like ChatGPT, Ope...

Investigating the effectiveness of an intraoperative decision support guided fluid therapy intervention on postoperative outcome of high-risk patients undergoing high-risk abdominal surgery: protocol for an international multicentre stepped-wedge cluster-randomised implementation trial.

BACKGROUND: Inappropriate fluid administration can impact patient outcome. Intraoperative advanced haemodynamic monitoring coupled with a treatment pr...

AI-delirium guard: Predictive modeling of postoperative delirium in elderly surgical patients.

INTRODUCTION: In older patients, postoperative delirium (POD) is a major complication that can result in greater morbidity, longer hospital stays, and...

Machine learning models for predicting severe acute kidney injury in patients with sepsis-induced myocardial injury.

Severe acute kidney injury (sAKI) is a prevalent and serious complication among patients with sepsis-induced myocardial injury (SIMI). Prompt and earl...

Model parameterization of robotic systems through the bio-inspired optimization.

The accurate modeling of dynamic systems, particularly robotic ones, is crucial in the industry. It enables simulation-based approaches that facilitat...

Development and validation of a risk prediction model for kinesiophobia in postoperative lung cancer patients: an interpretable machine learning algorithm study.

Kinesiophobia is particularly common in postoperative lung cancer patients, which causes patients may be reluctant to cough and move due to mispercept...

Artificial Intelligence Approach in Hip Prosthesis Identification and Addressing Radiographic Outcome Measures.

BACKGROUND: Radiographic assessment is crucial for the success of a hip arthroplasty procedure as a correctly positioned prosthesis indicates favorabl...