AIMC Topic: Retrospective Studies

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Can Simplified PADUA Renal (SPARE) Nephrometry scoring system help predict renal function outcomes after robot-assisted partial nephrectomy? (UroCCR study 93).

Minerva urology and nephrology
BACKGROUND: The SPARE Nephrometry Score (NS) is described as easier to implement than the RENAL and PADUA NSs, currently more widely used. Our objective was to compare the accuracy of SPARE NS in predicting renal function outcomes following RAPN.

Transitional zone prostate cancer: Performance of texture-based machine learning and image-based deep learning.

Medicine
This study is aimed to explore the performance of texture-based machine learning and image-based deep-learning for enhancing detection of Transitional-zone prostate cancer (TZPCa) in the background of benign prostatic hyperplasia (BPH), using a one-t...

[Robot-assisted PVP for the treatment of osteoporotic fractures of the upper thoracic vertebra].

Zhongguo gu shang = China journal of orthopaedics and traumatology
OBJECTIVE: To investigate the clinical effect of "Tianji" orthopedic robot-assisted percutaneous vertebro plasty(PVP) surgery in the treatment of upper thoracic osteoporotic fracture.

[Effectiveness of robot-guided percutaneous fixation and decompression via small incision for advanced thoracolumbar metastases].

Zhongguo xiu fu chong jian wai ke za zhi = Zhongguo xiufu chongjian waike zazhi = Chinese journal of reparative and reconstructive surgery
OBJECTIVE: To evaluate the effectiveness of robot-guided percutaneous fixation and decompression via small incision in treatment of advanced thoracolumbar metastases.

Prediction of postoperative complications after oesophagectomy using machine-learning methods.

The British journal of surgery
BACKGROUND: Oesophagectomy is an operation with a high risk of postoperative complications. The aim of this single-centre retrospective study was to apply machine-learning methods to predict complications (Clavien-Dindo grade IIIa or higher) and spec...

Natural Language Processing for the Identification of Incidental Lung Nodules in Computed Tomography Reports: A Quality Control Tool.

JCO global oncology
PURPOSE: To evaluate the diagnostic performance of a natural language processing (NLP) model in detecting incidental lung nodules (ILNs) in unstructured chest computed tomography (CT) reports.

Commercially Available Chest Radiograph AI Tools for Detecting Airspace Disease, Pneumothorax, and Pleural Effusion.

Radiology
Background Commercially available artificial intelligence (AI) tools can assist radiologists in interpreting chest radiographs, but their real-life diagnostic accuracy remains unclear. Purpose To evaluate the diagnostic accuracy of four commercially ...

Comparison of the Diagnostic Accuracy of Mammogram-based Deep Learning and Traditional Breast Cancer Risk Models in Patients Who Underwent Supplemental Screening with MRI.

Radiology
Background Access to supplemental screening breast MRI is determined using traditional risk models, which are limited by modest predictive accuracy. Purpose To compare the diagnostic accuracy of a mammogram-based deep learning (DL) risk assessment mo...

Robotic partial nephrectomy for renal tumor: The pentafecta outcomes of a single surgeon experience.

Asian journal of surgery
PURPOSE: This study investigated the oncological and functional surgical outcomes for patients with renal tumor who underwent robot-assisted partial nephrectomy (PN) by a single surgeon in Taiwan from 2006 to 2019.