AIMC Topic: Retrospective Studies

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Application of robot-assisted endoscopic technique in the treatment of patent ductus arteriosus in 106 children.

Journal of robotic surgery
The objective is to evaluate and apply the robot-assisted endoscopic surgical technique for treatment of patent ductus arteriosus (PDA) in children. Clinical data of 106 children with PDA who underwent robot-assisted endoscopic operation were retrosp...

Machine learning prediction of malignant middle cerebral artery infarction after mechanical thrombectomy for anterior circulation large vessel occlusion.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
OBJECTIVE: Prediction of malignant middle cerebral artery infarction (MMI) could identify patients for early intervention. We trained and internally validated a ML model that predicts MMI following mechanical thrombectomy (MT) for ACLVO.

Readmissions after radical nephrectomy in a national cohort.

Scandinavian journal of urology
OBJECTIVE: To analyze the factors and costs associated with 30-day readmissions for patients undergoing radical nephrectomy.

Deep-Learning and Device-Assisted Enteroscopy: Automatic Panendoscopic Detection of Ulcers and Erosions.

Medicina (Kaunas, Lithuania)
: Device-assisted enteroscopy (DAE) has a significant role in approaching enteric lesions. Endoscopic observation of ulcers or erosions is frequent and can be associated with many nosological entities, namely Crohn's disease. Although the application...

Deep learning for predicting the risk of immune checkpoint inhibitor-related pneumonitis in lung cancer.

Clinical radiology
AIM: To develop and validate a nomogram model that combines computed tomography (CT)-based radiological factors extracted from deep-learning and clinical factors for the early predictions of immune checkpoint inhibitor-related pneumonitis (ICI-P).

A Comparison of Percutaneous Pedicle Screw Accuracy Between Robotic Navigation and Novel Fluoroscopy-Based Instrument Tracking for Patients Undergoing Instrumented Thoracolumbar Surgery.

World neurosurgery
BACKGROUND: The accuracy of pedicle screws placed with instrument tracking and robotic navigation are individually comparable or superior to placement using standard fluoroscopy, however head-to-head comparisons between these adjuncts in a similar su...

Prediction of body weight from chest radiographs using deep learning with a convolutional neural network.

Radiological physics and technology
Accurate body weights are not necessarily available in routine clinical practice. This study aimed to investigate whether body weight can be predicted from chest radiographs using deep learning. Deep-learning models with a convolutional neural networ...

Same day discharge for robot-assisted radical prostatectomy: a prospective cohort study documenting an Australian approach.

ANZ journal of surgery
BACKGROUND: The introduction of robotic surgical systems has significantly impacted urological surgery, arguably more so than other surgical disciplines. The focus of our study was length of hospital stay - patients have traditionally been discharged...

Deep learning for collateral evaluation in ischemic stroke with imbalanced data.

International journal of computer assisted radiology and surgery
PURPOSE: Collateral evaluation is typically done using visual inspection of cerebral images and thus suffers from intra- and inter-rater variability. Large open databases of ischemic stroke patients are rare, limiting the use of deep learning methods...

Prediction of Visual Impairment in Epiretinal Membrane and Feature Analysis: A Deep Learning Approach Using Optical Coherence Tomography.

Asia-Pacific journal of ophthalmology (Philadelphia, Pa.)
PURPOSE: The aim was to develop a deep learning model for predicting the extent of visual impairment in epiretinal membrane (ERM) using optical coherence tomography (OCT) images, and to analyze the associated features.