AIMC Topic: Retrospective Studies

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Comparison of perioperative outcomes following transperitoneal versus retroperitoneal robot-assisted partial nephrectomy: a propensity-matched analysis of VCQI database.

World journal of urology
OBJECTIVE: To compare perioperative outcomes following retroperitoneal robot-assisted partial nephrectomy (RPRAPN) and transperitoneal robot-assisted partial nephrectomy (TPRAPN).

Can machine learning predict pharmacotherapy outcomes? An application study in osteoporosis.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The specific aim of this study is to develop machine learning models as a clinical approach for personalized treatment of osteoporosis. The model performance on outcome prediction was compared between four machine learning a...

Laparoscopic and robot-assisted ureterocalicostomy for treatment of primary and recurrent pelvi-ureteric junction obstruction in children: a multicenter comparative study with laparoscopic and robot-assisted Anderson-Hynes pyeloplasty.

International urology and nephrology
PURPOSE: This multi-institutional study aimed to assess the outcomes of laparoscopic ureterocalicostomy (LUC) and robot-assisted laparoscopic ureterocalicostomy (RALUC) and compare them with laparoscopic pyeloplasty (LP) and robot-assisted laparoscop...

Applying Deep Learning to Establish a Total Hip Arthroplasty Radiography Registry: A Stepwise Approach.

The Journal of bone and joint surgery. American volume
BACKGROUND: Establishing imaging registries for large patient cohorts is challenging because manual labeling is tedious and relying solely on DICOM (digital imaging and communications in medicine) metadata can result in errors. We endeavored to estab...

Automated diagnosis and prognosis of COVID-19 pneumonia from initial ER chest X-rays using deep learning.

BMC infectious diseases
BACKGROUND: Airspace disease as seen on chest X-rays is an important point in triage for patients initially presenting to the emergency department with suspected COVID-19 infection. The purpose of this study is to evaluate a previously trained interp...

Factors driving provider adoption of the TREWS machine learning-based early warning system and its effects on sepsis treatment timing.

Nature medicine
Machine learning-based clinical decision support tools for sepsis create opportunities to identify at-risk patients and initiate treatments at early time points, which is critical for improving sepsis outcomes. In view of the increasing use of such s...

Effectiveness of temporal subtraction computed tomography images using deep learning in detecting vertebral bone metastases.

European journal of radiology
PURPOSE: To assess the clinical effectiveness of temporal subtraction computed tomography (TS CT) using deep learning to improve vertebral bone metastasis detection.

Machine learning for multi-parametric breast MRI: radiomics-based approaches for lesion classification.

Physics in medicine and biology
In the artificial intelligence era, machine learning (ML) techniques have gained more and more importance in the advanced analysis of medical images in several fields of modern medicine. Radiomics extracts a huge number of medical imaging features re...

Generalizability of Deep Learning Segmentation Algorithms for Automated Assessment of Cartilage Morphology and MRI Relaxometry.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Deep learning (DL)-based automatic segmentation models can expedite manual segmentation yet require resource-intensive fine-tuning before deployment on new datasets. The generalizability of DL methods to new datasets without fine-tuning i...

Continuously sutured versus linear-stapled anastomosis in robot-assisted hybrid Ivor Lewis esophageal surgery following neoadjuvant chemoradiotherapy: a single-center cohort study.

Surgical endoscopy
BACKGROUND: Esophageal cancer surgery is technically highly demanding. During the past decade robot-assisted surgery has successfully been introduced in esophageal cancer treatment. Various techniques are being evaluated in different centers. In part...