Surgery

The use of artificial intelligence in reconstructive surgery for head and neck cancer: a systematic review.

OBJECTIVES: The popularity of artificial intelligence (AI) in head and neck cancer (HNC) management is increasing, but postoperative complications remain prevalent and are the main factor that impact prognosis after surgery. Hence, recent studies aim to assess new AI models to evaluate their ability to predict free flap complications more effectively than traditional algorithms. This systematic re...

Implementation of artificial intelligence-based computer vision model in laparoscopic appendectomy: validation, reliability, and clinical correlation.

BACKGROUND: Application of artificial intelligence (AI) in general surgery is evolving. Real-world implementation of an AI-based computer-vision model in laparoscopic appendectomy (LA) is presented. We aimed to evaluate (1) its accuracy in complexity grading and safety adherence, (2) clinical correlation to outcomes.

Development and validation of machine learning models and nomograms for predicting the surgical difficulty of laparoscopic resection in rectal cancer.

BACKGROUND: The objective of this study is to develop and validate a machine learning (ML) prediction model for the assessment of laparoscopic total m...

Prediction of coronary artery bypass graft outcomes using a single surgical note: An artificial intelligence-based prediction model study.

BACKGROUND: Healthcare providers currently calculate risk of the composite outcome of morbidity or mortality associated with a coronary artery bypass ...

Application of deep learning and radiomics in the prediction of hematoma expansion in intracerebral hemorrhage: a fully automated hybrid approach.

PURPOSE: Spontaneous intracerebral hemorrhage (ICH) is the most severe form of stroke. The timely assessment of early hematoma enlargement and its pro...

A Mouth and Tongue Interactive Device to Control Wearable Robotic Limbs in Tasks where Human Limbs Are Occupied.

The Wearable Robotic Limb (WRL) is a type of robotic arm worn on the human body, aiming to enhance the wearer's operational capabilities. However, pro...

Enhancing deep learning pre-trained networks on diabetic retinopathy fundus photographs with SLIC-G.

Diabetic retinopathy disease contains lesions (e.g., exudates, hemorrhages, and microaneurysms) that are minute to the naked eye. Determining the lesi...

Length of Stay Prediction Models for Oral Cancer Surgery: Machine Learning, Statistical and ACS-NSQIP.

OBJECTIVE: Accurate prediction of hospital length of stay (LOS) following surgical management of oral cavity cancer (OCC) may be associated with impro...

A machine learning approach for predicting textbook outcome after cytoreductive surgery and hyperthermic intraperitoneal chemotherapy.

INTRODUCTION: Peritoneal carcinomatosis is considered a late-stage manifestation of neoplastic diseases. Cytoreductive surgery with hyperthermic intra...

A Fast Online Elastic-Spine-Based Stiffness Adjusting Mechanism for Fishlike Swimming.

Fish tunes fishtail stiffness by coordinating its tendons, muscles, and other tissues to improve swimming performance. For robotic fish, achieving a f...

Endoscopic surgical field clarity index: An artificial intelligence-based measure of transnasal endoscopic surgical field quality.

Clear visualization during transnasal endoscopic surgery (TNES) is crucial for safe, efficient surgery. The endoscopic surgical field clarity index (E...

Machine learning applications in craniosynostosis diagnosis and treatment prediction: a systematic review.

Craniosynostosis refers to the premature fusion of one or more of the fibrous cranial sutures connecting the bones of the skull. Machine learning (ML)...

Prediction models for postoperative recurrence of non-lactating mastitis based on machine learning.

OBJECTIVES: This study aims to build a machine learning (ML) model to predict the recurrence probability for postoperative non-lactating mastitis (NLM...

From quantitative metrics to clinical success: assessing the utility of deep learning for tumor segmentation in breast surgery.

PURPOSE: Preventing positive margins is essential for ensuring favorable patient outcomes following breast-conserving surgery (BCS). Deep learning has...

Upper extremity contact pressure measurement in robot-assisted pelvic surgery.

Upper extremity complications are often a problem in robot-assisted pelvic surgery (RAPS) with the lithotomy-Trendelenburg position (LT-position). Thi...

The effects of different positions on lower extremity hemodynamics during robot-assisted laparoscopic radical prostatectomy for prostate cancer.

PURPOSE: This study aimed to investigate the effects of two different positions on lower extremity hemodynamics during robot-assisted laparoscopic rad...

Predicting Outcomes Following Lower Extremity Endovascular Revascularization Using Machine Learning.

BACKGROUND: Lower extremity endovascular revascularization for peripheral artery disease carries nonnegligible perioperative risks; however, outcome p...

Robot-assisted laparoscopic retroperitoneal donor nephrectomy: a safe and efficient improvement.

PURPOSE: Reducing operative injuries is important in living donor nephrectomy. The robot-assisted transperitoneal approach has some advantages than tr...

Utilising intraoperative respiratory dynamic features for developing and validating an explainable machine learning model for postoperative pulmonary complications.

BACKGROUND: Timely detection of modifiable risk factors for postoperative pulmonary complications (PPCs) could inform ventilation strategies that atte...

Development of a Two-Finger Haptic Robotic Hand with Novel Stiffness Detection and Impedance Control.

Haptic hands and grippers, designed to enable skillful object manipulation, are pivotal for high-precision interaction with environments. These techno...