Surgery

Latest AI and machine learning research in surgery for healthcare professionals.

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Using artificial intelligence to predict post-operative outcomes in congenital heart surgeries: a systematic review.

INTRODUCTION: Congenital heart disease (CHD) represents the most common group of congenital anomalie...

Machine learning to predict the decision to perform surgery in hepatic echinococcosis.

BACKGROUND: Cystic echinococcosis (CE) is a significant public health issue, primarily affecting the...

Neuropathology of focal epilepsy: the promise of artificial intelligence and digital Neuropathology 3.0.

Focal lesions of the human neocortex often cause drug-resistant epilepsy, yet ​surgical resection of...

Human Collaborative Control of Lower-Limb Prosthesis Based on Game Theory and Fuzzy Approximation.

For leg prosthesis user, the soft tissue and skin under the stump of are not accustomed to weight be...

Accuracy deficits during robotic time-constrained reaching are related to altered prefrontal cortex activity in children with cerebral palsy.

BACKGROUND: The prefrontal cortex (PFC) is an important node for action planning in the frontopariet...

Textbook outcome in liver surgery for intrahepatic cholangiocarcinoma: defining predictors of an optimal postoperative course using machine learning.

BACKGROUND: We sought to define textbook outcome in liver surgery (TOLS) for intrahepatic cholangioc...

Deep learning detected histological differences between invasive and non-invasive areas of early esophageal cancer.

The depth of invasion plays a critical role in predicting the prognosis of early esophageal cancer, ...

Predicting blood transfusion demand in intensive care patients after surgery by comparative analysis of temporally extended data selection.

BACKGROUND: Blood transfusion (BT) is a critical aspect of medical care for surgical patients in the...

Machine learning models predict the progression of long-term renal insufficiency in patients with renal cancer after radical nephrectomy.

BACKGROUND: Chronic Kidney Disease (CKD) is a common severe complication after radical nephrectomy i...

Stimulated Raman Histology and Artificial Intelligence Provide Near Real-Time Interpretation of Radical Prostatectomy Surgical Margins.

PURPOSE: Balancing surgical margins and functional outcomes is crucial during radical prostatectomy ...

SurgiTrack: Fine-grained multi-class multi-tool tracking in surgical videos.

Accurate tool tracking is essential for the success of computer-assisted intervention. Previous effo...

Development and Validation of an Explainable Prediction Model for Postoperative Recurrence in Pediatric Chronic Rhinosinusitis.

OBJECTIVE: This study aims to develop an interpretable machine learning (ML) predictive model to ass...

Spintronic Artificial Neurons Showing Integrate-and-Fire Behavior with Reliable Cycling Operation.

The rich dynamics of magnetic materials makes them promising candidates for neural networks that, li...

Artificial intelligence-enhanced magnetic resonance imaging-based pre-operative staging in patients with endometrial cancer.

OBJECTIVE: Evaluation of prognostic factors is crucial in patients with endometrial cancer for optim...

Expectations and Requirements of Surgical Staff for an AI-Supported Clinical Decision Support System for Older Patients: Qualitative Study.

BACKGROUND: Geriatric comanagement has been shown to improve outcomes of older surgical inpatients. ...

Machine learning for predicting post-operative outcomes in meningiomas: a systematic review and meta-analysis.

PURPOSE: Meningiomas are the most common primary brain tumour and account for over one-third of case...

Pixels to precision: Neuroradiology's leap into 3D printing for personalized medicine.

The realm of precision medicine, particularly its application within various sectors, shines notably...

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