Surgery

Whole-Body Transformation in Obese Patients Undergoing Metabolic Surgery: Insights From Automated Multiorgan Segmentation.

PURPOSE: This study assesses whether automated segmentation allows evaluation of subtle changes in volume and intrinsic tissue characteristics in an obese patient population undergoing metabolic surgery. MATERIALS AND METHODS: Multiorgan segmentation and intrinsic Hounsfield Unit (HU) analyses were performed in 1877 preoperative/postoperative computed tomography (CT) examinations, processing nine ...

Evidence-based AI clinical decision support system for acute burn care and complex reconstruction.

BACKGROUND: Burn surgery requires rapid, evidence-based decision-making across acute resuscitation, operative management, and reconstruction. Despite increasing interest in artificial intelligence (AI) for clinical decision support, no burn-specific system currently exists that provides transparent, citation-traceable guidance suitable for time-critical surgical care. METHODS: We developed BurnRAG...

[Expert consensus on the clinical application of robotic-assisted bronchoscopy].

Robotic-assisted bronchoscopy (RAB) is an emerging diagnostic and interventional technology which integrates thin-slice CT-based virtual airway recons...

Machine learning-driven design of engineered cilia enables hybrid operations in acoustic microrobots.

Microrobotic systems offer significant potential for precision medicine by enabling minimally invasive interventions in complex fluidic environments. ...

Predicting the Postoperative Recurrence Risk in Soft-Tissue Sarcomas of the Extremities and Trunk Using MRI-Based Nomogram.

RATIONALE AND OBJECTIVES: This study aims to develop a comprehensive nomogram for predicting the 3-year recurrence risk of patients with soft-tissue s...

Unveiling m7G modification patterns and causal drivers governing intracranial aneurysm rupture risk through multi-omics validation and m7G-MeRIP-seq profiling.

Intracranial aneurysm (IA) rupture causes severe brain hemorrhage with high mortality, yet its molecular drivers remain unclear and better risk predic...

Artificial intelligence-based approaches to augmenting and automating surgical training.

OBJECTIVE: To review recent advances in the use of artificial intelligence (AI) to address shortcomings in assessing and improving surgical performanc...

DDFU-Net: A Deep Decoder-Focused U-Net Model for Retinal Lesion Segmentation.

Early detection of retinal lesions helps to avoid visual loss or blindness. The main lesions associated with eye diseases include soft exudates, hard ...

Predicting the Future of Aesthetic Surgery: An Artificial Intelligence Framework for Global Publication Forecasting.

BACKGROUND: Artificial intelligence (AI) has transformed clinical decision making, yet its application to forecasting the evolution of surgical scienc...

CT Radiomics-Based Machine Learning Model for Predicting Capsular and Neural Invasion in Thyroid Carcinoma: Diagnostic Accuracy Study.

BACKGROUND: Thyroid carcinoma is the most prevalent endocrine malignancy, with a worldwide increasing incidence. Capsular invasion and neural invasion...

CT-based hybrid deep learning-radiomics framework for predicting postoperative rebleeding in hypertensive intracerebral hemorrhage.

OBJECTIVES: Hypertensive intracerebral hemorrhage (HICH) is a frequently encountered and highly lethal cerebrovascular disorder, and postoperative reb...

Comparative Evaluation of Robotic and Manual Bending of Clasps for Removable Partial Dentures.

INTRODUCTION AND AIMS: Conventional removable partial denture (RPD) clasp fabrication with wrought wire depends on operator skill, limiting efficiency...

SMC-LUD:Large-Scale B-Mode Liver Ultrasound Dataset for Hepatocellular Carcinoma and Hemangioma Classification.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality globally, and accurate classification of liver lesions using ultrasound ...

Validation of the Eyerobo FC Portable Fundus Camera for Diabetic Retinopathy Screening Using Public Datasets and Deep Learning.

INTRODUCTION: To validate the diagnostic performance of the Eyerobo FC, a new portable non-mydriatic fundus camera for diabetic retinopathy (DR) scree...

Influence of behavioural contingency on developmental song learning in young zebra finches (Taeniopygia guttata) tutored by a robot bird.

In humans and other animals, social robots can serve as effective tutors for learning new skills. Young oscines learn their song by imitating conspeci...

Pinostrobin attenuates microglia-mediated neuroinflammation after subarachnoid hemorrhage through modulation of the MYC-CTSL signaling axis.

Subarachnoid hemorrhage (SAH) is a life-threatening neurological emergency associated with high mortality and poor functional outcomes. Early brain in...

Implementation and learning curve in AI-assisted fluid management during abdominal oncologic surgery: a retrospective observational study.

BACKGROUND: Intraoperative fluid management during major abdominal oncologic surgery is complex and highly operator-dependent. Assisted Fluid Manageme...

Non-Neural Post-Thyroidectomy Dysphonia: Long-Term Voice Outcomes in 527 Patients.

OBJECTIVE: To characterize non-neural post-thyroidectomy dysphonia (PTD) by analyzing long-term voice outcomes in patients with no evidence of nerve i...

Letter to the Editor: Artificial intelligence in radiology: diagnostic sensitivity of ChatGPT for detecting hemorrhages in cranial computed tomography scans.

AI-Based Personalized Therapy With Clinical Intelligence and Radiomics (SPOILS) for Patients With Low Back Pain: Prospective Observational Study.

BACKGROUND: Low back pain (LBP) is a leading cause of disability worldwide, affecting people of all ages while showing increasing prevalence among you...