Latest AI and machine learning research in surgery for healthcare professionals.
PURPOSE: The use of neuronavigation with superimposed mapping tools has enabled visualization of key fiber tracts and improved peri-operative planning. However, a limitation of these approaches is their reliance on a static underlying brain atlas, particularly in neurosurgical patients with brain tumors. A tool that enables qualification and quantification of brain region connectivity could refine...
PURPOSE: Accurate interpretation of CT scans after pancreatic resection is crucial for detecting abnormalities, including postoperative complications and cancer recurrence. This study investigates the feasibility and clinical utility of a novel MKNet-family deep learning architecture for auto-segmentation of the residual pancreas on postoperative CT imaging, in comparison to previous approaches. M...
Artificial intelligence (AI) and machine learning (ML) are rapidly transforming surgery, moving beyond traditional risk prediction to real-time clinic...
BACKGROUND: Dynamic infrared thermography (DIRT) is increasingly being utilized for perforator selection and perfusion assessment in reconstructive mi...
The Accreditation Council for Graduate Medical Education (ACGME) recently conducted their 10-year specialty-specific revision of the colon and rectal ...
PURPOSE: To objectively quantify the motion paths of surgical instruments during cataract surgery across a resident's training, identifying patterns o...
Accurate anatomical segmentation in computed tomography (CT) imaging is vital for diagnostics and virtual surgical planning in head and neck surgery, ...
The invasiveness prediction in renal cell carcinoma (RCC) is of significant importance for the decision of clinical surgical plans and the patients' p...
Hereditary renal cell carcinoma (RCC) accounts for approximately 5-8% of all renal cancers. This review provides a comprehensive overview of the seven...
BACKGROUND: Aggressive recurrence (AR) is an important factor affecting prognosis after surgery for hepatocellular carcinoma (HCC). This study aimed t...
In maxillofacial surgery, orbital reconstruction requires precision to address both functional and aesthetic considerations arising from both acute an...
PURPOSE: Artificial intelligence (AI) emerged as a promising tool for enhancing healthcare delivery and outcomes for gastric cancer (GC) patients. Thi...
High-frequency ultrasound (HFUS) is valuable for assessing skin lesions, supporting diagnosis, treatment monitoring, and surgical planning. This study...
BACKGROUND: Artificial intelligence (AI) is increasingly applied in healthcare to support decision-making, personalize treatment, and improve outcomes...
BACKGROUND: Accurate monitoring of the depth of anaesthesia is essential for patient safety. Although processed electroencephalogram monitoring is wid...
BACKGROUND & AIMS: Microvascular invasion (MVI) is a key determinant of recurrence and poor outcomes in hepatocellular carcinoma (HCC), yet accurate p...
BackgroundAccurate intraoperative blood loss estimation is crucial, particularly for pediatric and adolescent patients. Traditional methods (visual, g...
BackgroundCommercially available large language models (LLMs) have demonstrated impressive capabilities in processing vast datasets and generating coh...
BACKGROUND: Implementing Mohs case complexity grading systems is critical due to inherent complexities of Mohs workflow coordination. Precise scheduli...
OBJECTIVE: Fenestrated-branched endovascular aortic repair (F-BEVAR) is a complex procedure that requires significant experience and advanced technica...