Latest AI and machine learning research in surgery for healthcare professionals.
BACKGROUND: Acute kidney injury (AKI) is a common complication following pediatric cardiac surgery, frequently leading to poor outcomes and even death in severe cases. Early prevention remains the primary intervention strategy. Studies have developed prediction models to identify at-risk children at an early stage. This study systematically evaluate existing AKI prediction models to support their ...
BACKGROUND: Lung adenocarcinoma presenting as ground-glass nodules (GGNs) comprises three invasive subtypes (adenocarcinoma in situ [AIS], minimally invasive adenocarcinoma [MIA], invasive adenocarcinoma [IAC]) with distinct prognoses and management strategies. Preoperative discrimination of these subtypes remains challenging for radiologists, and existing deep learning models rarely integrate mul...
BACKGROUND: Accurate grading and prognostic assessment of glioma requires integrating key molecular biomarkers, including IDH mutation status and the ...
BACKGROUND: While research on robotic rehabilitation has largely focused on evaluating device effectiveness, there remains a clear need to investigate...
BACKGROUND: Acute kidney injury (AKI) is a common and serious complication among hospitalized patients, and early risk stratification remains challeng...
BACKGROUND: Multidisciplinary tumor boards (MDTBs) play a central role in breast cancer management by integrating imaging findings with clinical and p...
BACKGROUND: Minimally invasive colorectal surgery is characterized by significant procedural variability, a difficult learning curve, and complication...
BACKGROUND: Artificial intelligence (AI) is increasingly applied to assess facial reanimation outcomes. However, its clinical utility and evidence hav...
Postoperative recurrence (POR) is a major challenge in the long-term management of Crohn's disease (CD), affecting up to 70% of patients within the fi...
BACKGROUND: Recently, advances in machine learning models have allowed for automatic and highly accurate detection of fractures. To date, however, no ...
PURPOSE: This study aimed to evaluate the utility of intratumoral and peritumoral radiomics derived from multi-parametric magnetic resonance imaging f...
BACKGROUND: This is Part II of a two-part series examining artificial intelligence (AI) in colorectal surgery. Part I established foundational concept...
Robotic surgery has evolved from a technological adjunct into a major platform for extending the reach of minimally invasive surgery (MIS). In contras...
Robot-assisted techniques have been increasingly explored in urolithiasis, particularly in selected complex settings such as concomitant reconstructio...
Search-and-Rescue (SAR) operations rely on sensor platforms to detect victims behind walls, obstacles etc. Conventional sensors (thermal, optical etc....
Compact robotic systems offer new opportunities for spinal procedures outside the operating room, but their potential for small-scale interventions su...
PURPOSE: VBT is increasingly being used in the lumbar spine to preserve mobility. Surgeons have noted differences in complications and outcomes among ...
PURPOSE: To develop and validate radiomics-based machine learning models combined with clinical parameters derived from venous phase contrast-enhanced...
OBJECTIVE: Magnetic resonance imaging (MRI) and computed tomography (CT) are commonly used to measure organ volumes, but accuracy has not been methodi...
BACKGROUND: Percutaneous endoscopic interlaminar discectomy (PEID) is a common surgical technique for lumbar disc herniation (LDH), but the risk facto...