A5034305639- Prostate Cancer Diagnosis and Treatment
- Radiomics and Machine Learning in Medical Imaging
- Prostate Cancer Treatment and Research
- MRI in cancer diagnosis
- Urologic and reproductive health conditions
- Anatomy and Medical Technology
- Artificial Intelligence in Healthcare and Education
- Surgical Simulation and Training
- Voice and Speech Disorders
- AI in cancer detection
- Advanced Radiotherapy Techniques
- Advanced X-ray and CT Imaging
- Advanced Technologies in Various Fields
- Systemic Sclerosis and Related Diseases
- Misinformation and Its Impacts
- Congenital Heart Disease Studies
- Ethics and Social Impacts of AI
- Central Venous Catheters and Hemodialysis
- Photoacoustic and Ultrasonic Imaging
- Digital Media Forensic Detection
- Mental Health and Psychiatry
- COVID-19 diagnosis using AI
- Soft Robotics and Applications
- Empathy and Medical Education
- Airway Management and Intubation Techniques
National Institutes of Health Clinical Center
2022-2025
Nvidia (United States)
2024
Singapore General Hospital
2024
National Institutes of Health
2022-2024
National Cancer Institute
2022-2024
National Institute of Biomedical Imaging and Bioengineering
2022
Background Data regarding the prospective performance of Prostate Imaging Reporting and System (PI-RADS) version 2.1 alone in combination with quantitative MRI features for prostate cancer detection is limited. Purpose To assess lesion-based clinically significant (csPCa) rates different PI-RADS categories to identify that could improve csPCa detection. Materials Methods This single-center study included men suspected or known who underwent multiparametric MRI/US-guided biopsy from April...
Background Multiparametric MRI (mpMRI) improves prostate cancer (PCa) detection compared with systematic biopsy, but its interpretation is prone to interreader variation, which results in performance inconsistency. Artificial intelligence (AI) models can assist mpMRI interpretation, large training data sets and extensive model testing are required. Purpose To evaluate a biparametric AI algorithm for intraprostatic lesion segmentation compare radiologist readings biopsy results. Materials...
Precise risk stratification through MRI/ultrasound (US) fusion-guided targeted biopsy (TBx) can guide optimal prostate cancer (PCa) management.
Background Image quality evaluation of prostate MRI is important for successful implementation into localized cancer diagnosis. Purpose To examine the impact image on detection using an in‐house previously developed artificial intelligence (AI) algorithm. Study Type Retrospective. Subjects 615 consecutive patients (median age 67 [interquartile range [IQR]: 61–71] years) with elevated serum PSA 6.6 [IQR: 4.6–9.8] ng/mL) prior to biopsy. Field Strength/Sequence 3.0T/T2‐weighted turbo‐spin‐echo...
Purpose To evaluate the performance of an artificial intelligence (AI) model in detecting overall and clinically significant prostate cancer (csPCa)-positive lesions on paired external in-house biparametric MRI (bpMRI) scans assess differences between each dataset. Materials Methods This single-center retrospective study included patients who underwent at institution were rescanned authors' May 2015 2022. A genitourinary radiologist performed prospective readouts following Prostate Imaging...
To determine whether the difference between MRI-based and ultrasound (US)-based volume measurements are associated with MRI/US-targeted fusion-guided biopsy outcomes. This retrospective, single-center study involved 4177 consecutive patients biopsied 2010 2023 using both fusion systematic biopsy. Biopsies were indicated because of elevated PSA levels or abnormal multiparametric MRI results. US calculated triplane ellipsoid formula, volumes obtained by semiautomatic planimetric segmentation....
Introduction Artificial intelligence (AI) models trained on audio data may have the potential to rapidly perform clinical tasks, enhancing medical decision-making and potentially improving outcomes through early detection. Existing technologies depend limited datasets collected with expensive recording equipment in high-income countries, which challenges deployment resource-constrained, high-volume settings where a profound impact health equity. Methods This report introduces novel protocol...
Abstract Purpose This study aimed to describe the workflow and evaluate accuracy of a novel smartphone augmented reality (AR) application that includes an integrated needle guide, in phantom. Materials Methods A cover with guide was designed 3D-printed. An AR for percutaneous developed, which projected path based on rigid guide. After planning using this tool, operator could place through reach target. Six lesions out-of-plane entry points were targeted abdominal Timing placements measured...
In this study, transcribed videos about personal experiences with COVID-19 were used for variant classification. The o1 LLM was to summarize the transcripts, excluding references dates, vaccinations, testing methods, and other variables that correlated specific variants but unrelated changes in disease. This step necessary effectively simulate model deployment early days of a pandemic when subtle symptomatology may be only viable biomarkers disease mutations. embedded summaries training...
Abstract Purpose Targeting accuracy determines outcomes for percutaneous needle interventions. Augmented reality (AR) in IR may improve procedural guidance and facilitate access to complex locations. This study aimed evaluate placement using a goggle-based AR system compared an ultrasound (US)-based fusion navigation system. Methods Six interventional radiologists performed 24 independent placements anthropomorphic phantom (CIRS 057A) four cohorts ( n = 6 each): (1) US-based fusion, (2) with...
Artificial intelligence (AI) methods have been proposed for the prediction of social behaviors that could be reasonably understood from patient-reported information. This raises novel ethical concerns about respect, privacy, and control over patient data. Ethical surrounding clinical AI systems behavior verification can divided into two main categories: (1) potential inaccuracies/biases within such systems, (2) impact on trust in patient-provider relationships with introduction automated...
The success of artificial intelligence in clinical environments relies upon the diversity and availability training data. In some cases, social media data may be used to counterbalance limited amount accessible, well-curated data, but this possibility remains largely unexplored. study, we mined YouTube collect voice from individuals with self-declared positive COVID-19 tests during time periods which Omicron was predominant variant 1,2,3 , while also sampling non-Omicron variants, other...
Large AI models trained on audio data may have the potential to rapidly classify patients, enhancing medical decision-making and potentially improving outcomes through early detection. Existing technologies depend limited datasets using expensive recording equipment in high-income, English-speaking countries. This challenges deployment resource-constrained, high-volume settings where a profound impact. report introduces novel type corresponding collection system that captures health guided...
The aim of this study was to assess the feasibility quantifying morphologic changes in tumors during immunotherapy, as a reflection response or survival.
You have accessJournal of UrologyCME1 Apr 2023MP38-09 TRACKING MRI-INVISIBLE LESIONS DURING ACTIVE SURVEILLANCE Daniel Nemirovsky, Zoe Blake, Jacob Enders, Alexander Kenigsberg, Neil Mendrihatta, Michael Rothberg, Daneshvar, Lindsey Hazen, Charisse Garcia, Sheng Xu, Baris Turkbey, Bradford Wood, Peter Pinto, and Sandeep Gurram NemirovskyDaniel Nemirovsky More articles by this author , BlakeZoe Blake EndersJacob Enders KenigsbergAlexander Kenigsberg MendrihattaNeil Mendrihatta RothbergMichael...
Abstract Purpose Our aims were to describe characteristic radiographic features of two power injectable medical access ports (MAPs) on various imaging modalities for rapid and precise identification; demonstrate the value this approach in identifying other types MAPs via “pictorial atlas”. Methods We analyzed commonly seen at our clinical center, Smart Port® CT-Injectable Port PowerPort® M.R.I.® Implantable Port. Photographs these retrospectively compared with identity-verified chest X-ray...