Surgery

Automatic image generation and stage prediction of breast cancer immunobiological through a proposed IHC-GAN model.

Invasive breast cancer diagnosis and treatment planning require an accurate assessment of human epidermal growth factor receptor 2 (HER2) expression levels. While immunohistochemical techniques (IHC) are the gold standard for HER2 evaluation, their implementation can be resource-intensive and costly. To reduce these obstacles and expedite the procedure, we present an efficient deep-learning model ...

Predicting the risk of gastroparesis in critically ill patients after CME using an interpretable machine learning algorithm - a 10-year multicenter retrospective study.

BACKGROUND: Gastroparesis following complete mesocolic excision (CME) can precipitate a cascade of severe complications, which may significantly hinder postoperative recovery and diminish the patient's quality of life. In the present study, four advanced machine learning algorithms-Extreme Gradient Boosting (XGBoost), Random Forest (RF), Support Vector Machine (SVM), and -nearest neighbor (KNN)-we...

Real-time isolation of physiological tremor using recursive singular spectrum analysis and random vector functional link for surgical robotics.

Hand-held robotic instruments enhance precision in microsurgery by mitigating physiological tremor in real time. Current tremor filtering algorithms i...

Preoperative prediction of the selection of the NOTES approach for patients with symptomatic simple renal cysts via an interpretable machine learning model: a retrospective study of 264 patients.

BACKGROUND: There are multiple surgical approaches for treating symptomatic simple renal cysts (SSRCs). The natural orifice transluminal endoscopic su...

Deep learning-based pelvimetry in pelvic MRI volumes for pre-operative difficulty assessment of total mesorectal excision.

BACKGROUND: Specific pelvic bone dimensions have been identified as predictors of total mesorectal excision (TME) difficulty and outcomes. However, ma...

Perspectives surrounding robotic total hip arthroplasty: a cross-sectional analysis using natural language processing.

BACKGROUND: Robotic technology has been used in total hip arthroplasty (THA) for several years. Despite the advances in this field, perspectives surro...

The combined evaluation of preoperative serum CEA and postoperative tissue CEA as a prognostic factor in stages 0-IV colorectal cancer: a retrospective cohort study.

BACKGROUND: The roles of preoperative serum carcinoembryonic antigen (sCEA) and postoperative tissue carcinoembryonic antigen (tCEA) have been extensi...

Prediction of early postoperative recurrence of hepatocellular carcinoma by habitat analysis based on different sequence of contrast-enhanced CT.

AIM: To develop a habitat imaging method for preoperative prediction of early postoperative recurrence of hepatocellular carcinoma.

Artificial Intelligence-Guided Inverse Design of Deployable Thermo-Metamaterial Implants.

Current limitations in implant design often lead to trade-offs between minimally invasive surgery and achieving the desired post-implantation function...

Varying pixel resolution significantly improves deep learning-based carotid plaque histology segmentation.

Carotid plaques-the buildup of cholesterol, calcium, cellular debris, and fibrous tissues in carotid arteries-can rupture, release microemboli into th...

Non-invasive blood glucose monitoring using PPG signals with various deep learning models and implementation using TinyML.

Accurate and continuous blood glucose monitoring is essential for effective diabetes management, yet traditional finger pricking methods are often inc...

Application of machine learning in predicting postoperative arrhythmia following transcatheter closure of perimembranous ventricular septal defects.

BACKGROUND: Arrhythmia is a frequent complication following transcatheter device closure of perimembranous ventricular septal defects (pmVSD). However...

Identification of common diagnostic genes and molecular pathways in endometriosis and systemic lupus erythematosus by machine learning approach and in vitro experiment.

Growing research suggests that endometriosis and systemic lupus erythematosus (SLE) are both chronic inflammatory diseases and closely related, but no...

Non-Invasive Diagnosis of Moyamoya Disease Using Serum Metabolic Fingerprints and Machine Learning.

Moyamoya disease (MMD) is a progressive cerebrovascular disorder that increases the risk of intracranial ischemia and hemorrhage. Timely diagnosis and...

Gripping Success Metric for Robotic Fruit Harvesting.

Recently, computer vision methods have been widely applied to agricultural tasks, such as robotic harvesting. In particular, fruit harvesting robots o...

Development and evaluation of a deep learning segmentation model for assessing non-surgical endodontic treatment outcomes on periapical radiographs: A retrospective study.

This study aimed to evaluate the performance of a deep learning-based segmentation model for predicting outcomes of non-surgical endodontic treatment....

Clinical utility of routine postoperative labs in emergency general surgery patients.

BACKGROUND: Morning postoperative labs are often obtained for emergency general surgery (EGS) patients. Studies in other surgical fields indicate that...

Viscum album, as alternative and bridge to palliative chemotherapy in recurrent gallbladder cancer following laparoscopic radical cholecystectomy: a case report.

A 78-year-old female patient was initially treated with laparoscopic radical cholecystectomy for gallbladder cancer (pT2aN1M0, stage IIIB). The patien...

Artificial intelligence in pancreaticobiliary endoscopy: Current applications and future directions.

Pancreaticobiliary endoscopy is an essential tool for diagnosing and treating pancreaticobiliary diseases. However, it does not fully meet clinical ne...

Assessing the value of deep neural networks for postoperative complication prediction in pancreaticoduodenectomy patients.

INTRODUCTION: Pancreaticoduodenectomy (PD) for patients with pancreatic ductal adenocarcinoma (PDAC) is associated with a high risk of postoperative c...