AIMC Topic: Retrospective Studies

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Robot-assisted partial nephrectomy in morbidly obese patients: a VCQI database study.

Journal of robotic surgery
To compare perioperative outcomes following robot-assisted partial nephrectomy (RAPN) in patients with morbid obesity (body mass index (BMI > 40 kg/m)) and non-obese patients. Using the Vattikuti Collective quality initiative (VCQI) database for RAPN...

Energy spectrum CT index-based machine learning model predicts the effect of intravenous thrombolysis in lower limbs.

Journal of applied clinical medical physics
To develop a noninvasive machine learning (ML) model based on energy spectrum computed tomography venography (CTV) indices for preoperatively predicting the effect of intravenous thrombolytic treatment in lower limbs. A total of 3492 slices containin...

Robot-assisted radical prostatectomy following holmium laser enucleation of the prostate: perioperative, functional, and oncological outcomes.

Journal of robotic surgery
Robot-assisted radical prostatectomy with previous holmium laser enucleation of the prostate is challenging, and few studies have analyzed its perioperative, functional, and oncological outcomes. Here we retrospectively evaluated 298 robot-assisted r...

Differential diagnosis of benign and malignant vertebral compression fractures: Comparison and correlation of radiomics and deep learning frameworks based on spinal CT and clinical characteristics.

European journal of radiology
PURPOSE: Differentiating benign from malignant vertebral compression fractures (VCFs) is a diagnostic dilemma in clinical practice. To improve the accuracy and efficiency of diagnosis, we evaluated the performance of deep learning and radiomics metho...

Deep learning for segmentation of the cervical cancer gross tumor volume on magnetic resonance imaging for brachytherapy.

Radiation oncology (London, England)
BACKGROUND: Segmentation of the Gross Tumor Volume (GTV) is a crucial step in the brachytherapy (BT) treatment planning workflow. Currently, radiation oncologists segment the GTV manually, which is time-consuming. The time pressure is particularly cr...

Prediction of Anemia From Cerebral Venous Sinus Attenuation on Deep-Learning Reconstructed Brain Computed Tomography Images.

Journal of computer assisted tomography
OBJECTIVE: The aim of the study is to evaluate whether the prediction of anemia is possible using quantitative analyses of unenhanced cranial computed tomography (CT) with deep learning reconstruction (DLR) compared with conventional methods.

Deep learning enables automatic adult age estimation based on CT reconstruction images of the costal cartilage.

European radiology
OBJECTIVE: Adult age estimation (AAE) is a challenging task. Deep learning (DL) could be a supportive tool. This study aimed to develop DL models for AAE based on CT images and compare their performance to the manual visual scoring method.

Active control time: an objective performance metric for trainee participation in robotic surgery.

Journal of robotic surgery
Trainee participation and progression in robotic general surgery remain poorly defined. Computer-assisted technology offers the potential to provide and track objective performance metrics. In this study, we aimed to validate the use of a novel metri...

Applying artificial intelligence algorithm in the design of a guide plate for mandibular angle ostectomy.

Journal of plastic, reconstructive & aesthetic surgery : JPRAS
PURPOSE: Surgical guide plates can improve the accuracy of surgery, although their design process is complex and time-consuming. This study aimed to use artificial intelligence (AI) to design standardized mandibular angle ostectomy guide plates and r...

Robot-Assisted Retroauricular Anterior Scalenectomy for Neurogenic Thoracic Outlet Syndrome.

Clinics in orthopedic surgery
BACKGROUND: This study described the surgical technique of a robot-assisted retroauricular anterior scalenectomy and assessed clinical outcomes and complications for patients with neurogenic thoracic outlet syndrome (nTOS).