Surgery

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

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Automated multiclass segmentation of liver vessel structures in CT images using deep learning approaches: a liver surgery pre-planning tool.

Accurate liver vessel segmentation is essential for effective liver surgery pre-planning, and reduci...

The association between cerebral small vessel disease and unfavorable hematoma morphology in primary intracerebral hemorrhage.

OBJECTIVE: To study the association between cerebral small vessel diseases (CSVD) and unfavorable he...

Impact of three-dimensional prostate models during robot-assisted radical prostatectomy on surgical margins and functional outcomes.

BACKGROUND: Robot-assisted radical prostatectomy (RARP) is the standard surgical procedure for the t...

Artificial intelligence-based action recognition and skill assessment in robotic cardiac surgery simulation: a feasibility study.

To create a deep neural network capable of recognizing basic surgical actions and categorizing surge...

AI-driven robotic surgery in oncology: advancing precision, personalization, and patient outcomes.

Artificial intelligence (AI) integrated with robotic systems is transforming oncologic surgery by si...

Prediction of gastrointestinal hemorrhage in cardiology inpatients using an interpretable XGBoost model.

Gastrointestinal bleeding (GIB) occurs more frequently in cardiovascular patients than in the genera...

Multimodal deep learning for cephalometric landmark detection and treatment prediction.

In orthodontics and maxillofacial surgery, accurate cephalometric analysis and treatment outcome pre...

Machine learning-based prediction of stone-free rate after retrograde intrarenal surgery for lower pole renal stones.

BACKGROUND: Lower pole renal stones (LPS) present unique challenges for retrograde intrarenal surger...

HNOSeg-XS: Extremely Small Hartley Neural Operator for Efficient and Resolution-Robust 3D Image Segmentation.

In medical image segmentation, convolutional neural networks (CNNs) and transformers are dominant. F...

Evaluating the Accuracy and Readability of ChatGPT in Addressing Patient Queries on Adult Spinal Deformity Surgery.

Study DesignCross-Sectional.ObjectivesAdult spinal deformity (ASD) affects 68% of the elderly, with ...

Current Applications and Limitations of Augmented Reality in Urological Surgery: A Practical Primer and 'State of the Field'.

PURPOSE OF REVIEW: To provide a primer for how augmented reality (AR)-guided surgical technology wor...

[Validation of artificial intelligence algorithms for the surgical practice].

BACKGROUND: Artificial intelligence (AI) is increasingly being used in surgery; however, the validat...

Human and animal models for studying hemorrhagic shock.

BACKGROUND: Studying the physiological response to severe hemorrhage remains challenging in real-wor...

Machine learning analysis of survival outcomes in breast cancer patients treated with chemotherapy, hormone therapy, surgery, and radiotherapy.

Breast cancer continues to be a leading cause of death among women in the world. The prediction of s...

Machine learning models predict risk of lower extremity deep vein thrombosis in hospitalized patients with spontaneous intracerebral hemorrhage.

Lower extremity deep vein thrombosis is one of the important complications of spontaneous intracereb...

Autoimmune gastritis detection from preprocessed endoscopy images using deep transfer learning and moth flame optimization.

Gastric Tract Disease (GTD) constitutes a medical emergency, emphasizing the critical importance of ...

Genome sequencing is critical for forecasting outcomes following congenital cardiac surgery.

While exome and whole genome sequencing have transformed medicine by elucidating the genetic underpi...

Acute Management of Nasal Bone Fractures: A Systematic Review and Practice Management Guideline.

Nasal bone fractures represent the most common facial skeletal injury, challenging both function and...

Multi-class subarachnoid hemorrhage severity prediction: addressing challenges in predicting rare outcomes.

Accurately predicting the severity of subarachnoid hemorrhage (SAH) is critical for informing clinic...

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