A5055415605- Bladder and Urothelial Cancer Treatments
- Colorectal Cancer Screening and Detection
- Urinary and Genital Oncology Studies
- Urological Disorders and Treatments
- Pediatric Urology and Nephrology Studies
- Prostate Cancer Diagnosis and Treatment
- Urologic and reproductive health conditions
- Cardiac, Anesthesia and Surgical Outcomes
- Sexual function and dysfunction studies
- Digital Radiography and Breast Imaging
- Surgical Simulation and Training
- Pelvic floor disorders treatments
- Kidney Stones and Urolithiasis Treatments
- Esophageal Cancer Research and Treatment
- MRI in cancer diagnosis
- Urinary Bladder and Prostate Research
- Anesthesia and Pain Management
- Prostate Cancer Treatment and Research
- Radiomics and Machine Learning in Medical Imaging
- Opioid Use Disorder Treatment
- Paleopathology and ancient diseases
- Ovarian function and disorders
- Dermatological and COVID-19 studies
- Patient Satisfaction in Healthcare
- Innovations in Medical Education
Stanford University
2016-2024
Stanford Medicine
2018-2024
VA Palo Alto Health Care System
2019-2023
University of California, Los Angeles
2013-2017
Background and Purpose: Classically, abdominal X-ray (KUB), ultrasound, or a combination of both have been routinely used for ureteral stone surveillance after initial diagnosis. More recently, ultra-low-dose CT (ULD CT) has emerged as technique that reduces radiation dose while maintaining high sensitivity specificity urinary detection. We aim to evaluate our experience with ULD patients ureterolithiasis, measuring real-world doses detection performance. Methods: reviewed all scans...
A bioinspired system enables rapid, near-patient urine testing for metabolic evaluation of stone formers.
Background: Detection of bladder tumors under white light cystoscopy (WLC) is challenging yet impactful on treatment outcomes. Artificial intelligence (AI) holds the potential to improve tumor detection; however, its application in real-time setting remains unexplored. AI has been applied previously recorded images for post hoc analysis. In this study, we evaluate feasibility integration during clinic and transurethral resection (TURBT) live, streaming video. Methods: Patients undergoing...
Abstract Objective. Accurate tumor detection is critical in cystoscopy to improve bladder cancer resection and decrease recurrence. Advanced deep learning algorithms hold the potential performance of standard white-light (WLC) a noninvasive cost-effective fashion. The purpose this work develop cost-effective, transformer-augmented algorithm for accurate tumors WLC assess its on archived patient data. Approach. ‘CystoNet-T’, learning-based detector, was developed with pyramidal CNN...
There are few markers to identify those likely recur or progress after treatment with intravesical bacillus Calmette-Guérin (BCG). We developed and validated artificial intelligence-based histologic assays that extract interpretable features from transurethral resection of bladder tumor digitized pathology images predict risk recurrence, progression, development BCG-unresponsive disease, cystectomy.
Introduction: Minimally invasive surgery offers reduced pain and opioid use postoperatively compared with open surgery, but large-scale comparative studies are lacking. We assessed the incidence of persistent after robot-assisted radical prostatectomy (RARP). Materials Methods: performed a retrospective claims database cohort study opioid-naive (i.e., no prescriptions 30–180 days before index surgery) adult males who underwent for prostate cancer from July 2013 to June 2017. For patients...
While Fontan palliation in the form of total cavopulmonary connection has improved management congenital single ventricle physiology, long-term outcomes for patients with this disease are suboptimal due to lack two functional ventricles. Researchers have shown that ventricular assist devices (VADs) can normalize hemodynamics. To minimize blood contacting surfaces VAD, we evaluated use an external compression device (C-Pulse Heart Assist System, Sunshine Inc.) as a device. A mock circulation...
Background: Prognostication is essential to determine the risk profile of patients with urologic cancers. Methods: We utilized SEER national cancer registry database approximately 2 million diagnosed cancers (penile, testicular, prostate, bladder, ureter, and kidney). The cohort was randomly divided into development set (90%) out-held test (10%). Modeling algorithms clinically relevant parameters were for cancer-specific mortality prognosis. model fitness survival estimation assessed using...
Background: Cystoscopy is a common endoscopic procedure to examine the lower urinary tract, particularly bladder, for potential tumors, lesions, or other sources of hematuria. has recognized shortcomings including missed tumors and differentiation benign from cancerous lesions. Clinical outcomes are affected by variable provider experience. Deep learning models have been proposed address these issues. Because real-time cystoscopy consists sequential frames, we explored novel class DL...
You have accessJournal of UrologySunday Next Frontier (LBA)1 Apr 2019LBA-20 AUTOMATED CYSTOSCOPIC DETECTION OF BLADDER CANCER USING DEEP-LEARNING Eugene Shkolyar*, Xiao Jia, Lei Xing, and Joseph Liao Shkolyar*Eugene Shkolyar* , JiaXiao Jia XingLei Xing LiaoJoseph View All Author Informationhttps://doi.org/10.1097/01.JU.0000557512.76700.42AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVES:...
Abstract Clostridium septicum is a spore-forming anaerobic gram-positive rod capable of causing rapidly progressive nontraumatic myonecrosis. A case C. myonecrosis (ntCSM) described. systematic review all published cases ntCSM from 2000–2015 was performed. Twenty-three were identified. The median age 67 years (range, 26–84 years) and 15 (68%) men. Only 5 (21%) patients had multifocal disease. Diabetes mellitus the most common preexisting medical condition present in 9 (39%) patients. Occult...
Adequate lesion detection is critical in cystoscopy to improve bladder cancer resection and decrease recurrence. In particular, flat-appearing such as carcinoma situ difficult discern by standard white-light (WLC). The adoption of blue-light (BLC), an adjunct imaging technique, remains modest due the expensive equipment required. We developed a deep-learning algorithm, CystoNet-F, for augmented flat lesions on WLC. CystoNet-F was designed augment WLC incorporating domain translation...
PURPOSE Development of intelligence systems for bladder lesion detection is cost intensive. An efficient strategy to develop such solutions needed. MATERIALS AND METHODS We used four deep learning models (ConvNeXt, PlexusNet, MobileNet, and SwinTransformer) covering a variety model complexity efficacy. trained these on previously published educational cystoscopy atlas (n = 312 images) estimate the ratio between normal cancer scores externally validated videos from 68 cases, with region...