Surgery

Technical advancements in robot-assisted radical prostatectomy: systematic review and bibliometric analysis.

Robot-assisted radical prostatectomy has transformed the surgical management of localized prostate cancer, yet its research landscape remains incompletely mapped. We conducted a systematic review and bibliometric analysis of 578 articles and conference papers from Scopus and Web of Science (2005-2026), following PRISMA guidelines, and analyzed publication trends, geographic and institutional distr...

Artificial intelligence-based model for identifying anatomical and surgical structures in the videos of laparoscopic left hemicolectomy.

BACKGROUND: Precise surgical procedures are critical to improving the survival outcomes for colon cancer patients. Currently, there is no dedicated intraoperative navigation system available for performing precise surgery. OBJECTIVE: We aimed to innovate an artificial intelligence-based model for identifying anatomical structures and surgical instruments during laparoscopic left hemicolectomy, to ...

Explainable machine learning for automated robotic surgical skill assessment using rich kinematic features.

Robotic-assisted surgery (RAS) extends minimally invasive surgery by restoring dexterity, tremor filtration, and ergonomic console control compared wi...

Mapping the global landscape of robot-assisted hernia surgery research: a bibliometric analysis.

To characterize the worldwide body of literature on robot-assisted hernia surgery through bibliometric and scientometric approaches, and to clarify it...

Clinical Evaluation of an AI-Assisted Decision Support System for General Anesthesia Management Based on Data From 6 Centers: Comparative Study.

BACKGROUND: AI is rapidly transforming medical practice, with emerging applications in perioperative care and anesthesiology. However, the clinical im...

Pre-operative concerns and post-operative satisfaction: comparing attitudes toward bariatric surgery and medication intervention for weight loss on Reddit.

BACKGROUND: Patient perceptions influence the success of bariatric surgery and pharmacologic weight loss therapies, yet many concerns never reach prov...

Interpretable multimodal deep learning for time-resolved survival prediction after hepatocellular carcinoma resection.

Hepatocellular carcinoma (HCC) exhibits substantial interpatient heterogeneity, leading to markedly variable outcomes and survival even among patients...

AI-assisted decision support for sickle cell disease severity stratification using routine blood tests: a systematic review and meta-analysis.

BACKGROUND: Stratifying sickle cell disease (SCD) severity remains challenging, particularly in resource-limited settings. Artificial intelligence (AI...

Beyond visual inspection: can a multimodal machine learning model improve the preoperative differentiation of endometrial polyps from non-polypoid endometrial lesions?

OBJECTIVE: To develop a multimodal machine learning model that integrates clinical data and ultrasound features to improve the non‑invasive preoperati...

[Overview and conclusions of the STROKE data platform of the National Laboratory for Translational Neuroscience and the associated clinical studies].

Acute ischemic and hemorrhagic stroke are among the leading causes of mortality and long-term disability worldwide. In addition to the results of rand...

A clinically interpretable model for predicting pharyngocutaneous fistula after total laryngectomy.

BACKGROUND: Pharyngocutaneous fistula (PCF) is a frequent complication following total laryngectomy. While various risk models exist, their practical ...

Construction and validation of a nomogram prediction model for postoperative residual risk of pediatric obstructive sleep apnea based on OCTA and LASSO machine learning algorithm.

OBJECTIVE: To evaluate the value of retinal optical coherence tomography angiography (OCTA) microcirculatory parameters combined with clinical, bioche...

Clinically meaningful risk factors for recurrence in T1 colorectal cancer treated with endoscopic resection alone identified by unsupervised machine learning: a multicenter study.

BACKGROUND AND STUDY AIM: Identifying high-risk patients for recurrence after endoscopic resection (ER) of T1 colorectal cancer (CRC) remains challeng...

WFUMB Liver Ultrasound Fusion Imaging Technical Review and Position Statement: Focus on CT/MRI-Based Fusion.

OBJECTIVE: Ultrasound fusion imaging is a hybrid technique that combines real-time ultrasonography (US) with pre-acquired computed tomography (CT) or ...

Research landscape of robot-assisted reconstructive and plastic surgery.

Robot-assisted technologies have progressively transformed plastic and reconstructive surgery by enabling enhanced precision, minimally invasive acces...

Radiomic model with SHAP-based interpretability for predicting invasiveness of pure ground-glass nodules: a retrospective study based on high-resolution computed tomography (HRCT) volumetric datasets.

BACKGROUND: Radiomics holds promise for lung cancer diagnosis. This study developed an interpretable radiomics-clinical model to predict the invasiven...

Habitat-based imaging and peritumoral radiomics on ultrasound images for predicting lymphovascular invasion in breast invasive ductal carcinoma: a two-center study.

PURPOSE: This study aimed to evaluate the feasibility of employing habitat-based radiomic distributions in ultrasound (US) images to quantitatively ch...

Predicting postoperative coronal imbalance in Lenke 1/2 adolescent idiopathic scoliosis: A machine learning model with clinical interpretability.

OBJECTIVES: Selective posterior thoracic fusion (sPTF) for Lenke 1/2 adolescent idiopathic scoliosis (AIS) aims to reconcile multi-planar correction w...

Methodological quality and performance of artificial intelligence and machine learning models for preoperative risk prediction in plastic surgery: A systematic review.

Artificial intelligence (AI) and machine learning (ML) are increasingly being applied to preoperative risk prediction in plastic surgery; however, the...

A serum-clinical composite model for prostate cancer diagnosis: multicenter validation and CRISPR/Cas13a-based detection.

BACKGROUND: Avoidable prostate biopsies remain a persistent weakness of prostate specific antigen (PSA)- and imaging-led prostate cancer (PCa) diagnos...