Surgery

A novel nomogram based on machine learning predicting overall survival for hepatocellular carcinoma patients with dynamic α‑fetoprotein level changes after local resection.

The principal aim of the present study was to develop and validate a nomogram predicting overall survival (OS) in patients with α-fetoprotein (AFP)-negative hepatocellular carcinoma (AFP-NHCC) who experience dynamic changes in AFP level after hepatectomy. A cohort of 870 patients were enrolled and randomly assigned into a training cohort (n=600) and a validation cohort (n=270) at a 7:3 ratio. The ...

Preoperative submaximal cardiopulmonary exercise testing and its association with early postoperative complications.

BACKGROUND: Early postoperative complication risk prediction would enhance perioperative surveillance and resource allocation. Reports have described brief submaximal cardiopulmonary exercise testing (CPET) for the routine assessment of cardiopulmonary disease. Compared with conventional CPET, it can be performed in 6 min and is used to predict peak CPET measurements. We aimed to determine whether...

Generalizability of Artificial Intelligence Assessments in Laparoscopic Surgery Simulation.

INTRODUCTION: The application of artificial intelligence (AI) in the assessment of procedural skills on a simulation platform using the global rating ...

Identification of pivotal genes and regulatory networks associated with SAH based on multi-omics analysis and machine learning.

Subarachnoid hemorrhage (SAH) is a disease with high mortality and morbidity, and its pathophysiology is complex but poorly understood. To investigate...

Predicting outcomes following open abdominal aortic aneurysm repair using machine learning.

Patients undergoing open surgical repair of abdominal aortic aneurysm (AAA) have a high risk of post-operative complications. However, there are no wi...

Single Joint Hybrid Assistive Limb (HAL-SJ) robotic exoskeleton therapy in improving functional outcomes among workers with wrist fractures: Study protocol for a randomized controlled trial.

INTRODUCTION: Robotic technologies have been developed for motor rehabilitation and such robots have shown favourable results when compared with equiv...

Identification of immune-related biomarkers and immune infiltrations of intracranial aneurysm with subarachnoid hemorrhage by machine-learning strategies.

Background: Subarachnoid hemorrhage (SAH) risk increases with intracranial aneurysms (IA), but their relationship remains unclear. Methods: We explore...

Development of a Low-Profile, Piezoelectric Robot for MR-Guided Abdominal Needle Interventions.

PURPOSE: Minimally invasive needle-based interventions are commonly used in cancer diagnosis and treatment, including procedures, such as biopsy, brac...

Evaluating Large Language Model's accuracy in current procedural terminology coding given operative note templates across various plastic surgery sub-specialties.

BACKGROUND: Manual CPT coding from operative notes is a time-intensive process that adds to the administrative burden in healthcare. Large Language Mo...

Biomimetic rigid-soft finger design for highly dexterous and adaptive robotic hands.

In dexterous robotic hand design, achieving high mobility and adaptability comparable to human hands remains an ongoing challenge. Biomimetic designs ...

SegMatch: semi-supervised surgical instrument segmentation.

Surgical instrument segmentation is recognised as a key enabler in providing advanced surgical assistance and improving computer-assisted intervention...

Clinical performance of a machine learning-based model for detecting lymph node metastasis in papillary thyroid carcinoma: A multicenter study.

Papillary thyroid carcinoma (PTC) is a common endocrine malignancy with a generally favorable prognosis, but lymph node metastasis (LNM) complicates t...

Bridging surgical oncology and personalized medicine: the role of artificial intelligence and machine learning in thoracic surgery.

Lung cancer remains the leading cause of cancer-related deaths globally, often detected in advanced stages with poor prognosis. While surgical resecti...

Miniaturized soft growing robots for minimally invasive surgeries: challenges and opportunities.

Advancements in assistive robots have significantly transformed healthcare procedures in recent years. Clinical continuum robots have enhanced minimal...

Efficient control of spider-like medical robots with capsule neural networks and modified spring search algorithm.

This study introduces an innovative method for gesture recognition in medical robotics, utilizing Capsule Neural Networks (CNNs) in conjunction with t...

Screening risk factors for the occurrence of wedge effects in intramedullary nail fixation for intertrochanteric fractures in older people via machine learning and constructing a prediction model: a retrospective study.

PURPOSE: The wedge effect (V-effect) is a common complication in intramedullary nailing surgery for intertrochanteric fractures and can significantly ...

Early operative difficulty assessment in laparoscopic cholecystectomy via snapshot-centric video analysis.

PURPOSE: Laparoscopic cholecystectomy (LC) operative difficulty (LCOD) is highly variable and influences outcomes. Despite extensive LC studies in sur...

AO Spine Clinical Practice Recommendations for Diagnosis and Management of Degenerative Cervical Myelopathy: Evidence Based Decision Making - A Review of Cutting Edge Recent Literature Related to Degenerative Cervical Myelopathy.

Study DesignLiterature review of key topics related to degenerative cervical myelopathy (DCM) with critical appraisal and clinical recommendations.Obj...

Using the Geriatric Emergency Perioperative Risk Index Derived From Artificial Intelligence Algorithms to Predict Outcomes of Geriatric Emergency General Surgery.

INTRODUCTION: The objective of this study was to employ artificial intelligence (AI) technology for the development of a model that can accurately for...

Predicting Weight Loss Success After Gastric Sleeve Surgery: A Machine Learning-Based Approach.

BACKGROUND/OBJECTIVES: Obesity is a global health issue, and in this context, bariatric surgery is considered the most effective treatment for severe ...