Latest AI and machine learning research in surgery for healthcare professionals.
Recently, there has been a significant increase in the number of foot diseases, highlighting the imp...
PURPOSE: Awake craniotomy presents a unique opportunity to map and preserve critical brain functions...
INTRODUCTION: Surgical patients frequently experience post-operative complications at home. Digital ...
The prognosis following radical surgery for intrahepatic cholangiocarcinoma (ICC) is poor, and optim...
BACKGROUND: Symptomatic intracranial hemorrhage (sICH) after mechanical thrombectomy (MT) is associa...
Early prediction of poor outcomes in patients impacted with aneurysmal subarachnoid hemorrhage (aSAH...
The aim of this study was to develop and validate a convolutional neural network (CNN) algorithm for...
PURPOSE: Accurate and automated early survival prediction is critical for patients with glioblastoma...
The prediction of brain cancer occurrence and risk assessment of brain hemorrhage using a hybrid dee...
The ability to recover tissue deformation from surgical video is fundamental for many downstream app...
Endoscopic-assisted breast surgery (EABS) provides better cosmetic outcomes for breast cancer patie...
Here, we explore the transformative effects of artificial intelligence (AI) and large language model...
Machine Learning (ML) techniques require novel computer programming skills along with clinical domai...
Pharmaceutical and biotechnology companies are increasingly being challenged to shorten the cycle ti...
BACKGROUND: Treatment of locally advanced rectal cancer (LARC) involves neoadjuvant chemoradiotherap...
The exploration of adaptive robotic systems capable of performing complex tasks in unstructured envi...
This article proposes a model-free kinematic control method with predefined-time convergence for rob...
INTRODUCTION: The postoperative recurrence of gastric cancer (GC) has a significant impact on the ov...
BACKGROUND: Laparoscopic cholecystectomy (LC) is the gold standard for treating symptomatic gallston...
Deep learning models have emerged as rapid, accurate, and effective approaches for clinical decision...
This study aimed to develop and validate a machine learning (ML)-based model for predicting liposuct...