Urology

Clinically Applicable Machine Learning Approaches to Identify Attributes of Chronic Kidney Disease (CKD) for Use in Low-Cost Diagnostic Screening.

OBJECTIVE: Chronic kidney disease (CKD) is a major public health concern worldwide. High costs of late-stage diagnosis and insufficient testing facilities can contribute to high morbidity and mortality rates in CKD patients, particularly in less developed countries. Thus, early diagnosis aided by vital parameter analytics using affordable computer-aided diagnosis could not only reduce diagnosis co...

Characterizing chronological accumulation of comorbidities in healthy veterans: a computational approach.

Understanding patient accumulation of comorbidities can facilitate healthcare strategy and personalized preventative care. We applied a directed network graph to electronic health record (EHR) data and characterized comorbidities in a cohort of healthy veterans undergoing screening colonoscopy. The Veterans Affairs Cooperative Studies Program #380 was a prospective longitudinal study of screening ...

Simpson's Paradox in COVID-19 Case Fatality Rates: A Mediation Analysis of Age-Related Causal Effects.

We point out an instantiation of Simpson's paradox in COVID-19 case fatality rates (cfrs): comparing a large-scale study from China (February 17) with...

Impact of Surgeon-Controlled Suction During Robotic Prostatectomy to Reduce Dependence on Bedside Assistance.

Suction during robotic surgery has traditionally been performed by a bedside assistant. Adequately skilled assistants are not always available. We as...

Survival Analysis Using Surgeon Skill Metrics and Patient Factors to Predict Urinary Continence Recovery After Robot-assisted Radical Prostatectomy.

BACKGROUND: It has been shown that metrics recorded for instrument kinematics during robotic surgery can predict urinary continence outcomes.

Autosegmentation of Prostate Zones and Cancer Regions from Biparametric Magnetic Resonance Images by Using Deep-Learning-Based Neural Networks.

The accuracy in diagnosing prostate cancer (PCa) has increased with the development of multiparametric magnetic resonance imaging (mpMRI). Biparametri...

Uncertainty-aware temporal self-learning (UATS): Semi-supervised learning for segmentation of prostate zones and beyond.

Various convolutional neural network (CNN) based concepts have been introduced for the prostate's automatic segmentation and its coarse subdivision in...

Comparison of Perioperative, Oncological, and Functional Outcomes of Three-Dimensional Versus Robot-Assisted Laparoscopic Radical Prostatectomy: A Preliminary Study.

Radical prostatectomy (RP) is the first-line treatment modality for prostate cancer and can be performed using retropubic or minimally invasive techn...

Robot-assisted Cystectomy with Intracorporeal Urinary Diversion After Pelvic Irradiation for Prostate Cancer: Technique and Results from a Single High-volume Center.

BACKGROUND: Radiation therapy (RT) for prostate cancer (PCa) treatment is burdened by high rates of late urinary adverse events (UAEs). The feasibilit...

"Early-pull-out" technique for intracorporeal ileal conduit urinary diversion after robot-assisted radical cystectomy.

Deep learning-based molecular morphometrics for kidney biopsies.

Morphologic examination of tissue biopsies is essential for histopathological diagnosis. However, accurate and scalable cellular quantification in hum...

Role of AI and Histopathological Images in Detecting Prostate Cancer: A Survey.

Prostate cancer is one of the most identified cancers and second most prevalent among cancer-related deaths of men worldwide. Early diagnosis and trea...

Deep learning-based auto-segmentation of organs at risk in high-dose rate brachytherapy of cervical cancer.

BACKGROUND AND PURPOSE: Delineation of organs at risk (OARs), such as the bladder, rectum and sigmoid, plays an important role in the delivery of opti...

Machine learning-based investigation of the cancer protein secretory pathway.

Deregulation of the protein secretory pathway (PSP) is linked to many hallmarks of cancer, such as promoting tissue invasion and modulating cell-cell ...

Editorial for "A Deep Learning Approach to Diagnostic Classification of Prostate Cancer Using Pathology-Radiology Fusion".

Comparison of plasma neutrophil gelatinase-associated lipocalin (NGAL) levels after robot-assisted laparoscopic and retropubic radical prostatectomy: an observational study.

BACKGROUND AND OBJECTIVES: Patients undergoing radical prostatectomy are at increased risk of Acute Kidney Injury (AKI) because of intraoperative blee...

Derivation and validation of a machine learning risk score using biomarker and electronic patient data to predict progression of diabetic kidney disease.

AIM: Predicting progression in diabetic kidney disease (DKD) is critical to improving outcomes. We sought to develop/validate a machine-learned, progn...

Prediction of risk of acquiring urinary tract infection during hospital stay based on machine-learning: A retrospective cohort study.

BACKGROUND: Healthcare associated infections (HAI) are a major burden for the healthcare system and associated with prolonged hospital stay, increased...

Effect of a novel technique of posterior reconstruction of pubourethralis on 'early' return of continence after robot assisted radical prostatectomy (RARP): A comparative study.

OBJECTIVE: To study the after robot assisted radical prostatectomy (RARP).

An independent assessment of an artificial intelligence system for prostate cancer detection shows strong diagnostic accuracy.

Prostate cancer is a leading cause of morbidity and mortality for adult males in the US. The diagnosis of prostate carcinoma is usually made on prosta...