Urology

Comparison of CBCT-based dose calculation methods in head and neck cancer radiotherapy: from Hounsfield unit to density calibration curve to deep learning.

PURPOSE: Anatomical variations occur during head and neck (H&N) radiotherapy treatment. kV cone-beam computed tomography (CBCT) images can be used for daily dose monitoring to assess dose variations owing to anatomic changes. Deep learning methods (DLMs) have recently been proposed to generate pseudo-CT (pCT) from CBCT to perform dose calculation. This study aims to evaluate the accuracy of a DLM ...

Minimally invasive simple prostatectomy in the era of laser enucleation for high-volume prostates: A systematic review and meta-analysis.

OBJECTIVE: To perform a systematic review and meta-analysis of available prospective and retrospective studies comparing the minimally invasive (laparoscopic or robot-assisted) simple prostatectomy (MISP) and laser enucleation of the prostate for treating male lower urinary tract symptoms in high-volume prostates, as laser enucleation of the prostate is the new trend for treating high-volume prost...

The Silent Operation Theatre Optimisation System (SOTOS) to reduce noise pollution during da Vinci robot-assisted laparoscopic radical prostatectomy.

To reduce noise pollution and consequently stress during robot-assisted laparoscopic radical prostatectomy (RALP) the aim of our study was to evaluate...

Performance of Ga-68 PSMA PET/CT for diagnosis and grading of local prostate cancer.

BACKGROUND: We aimed to evaluate the utility of prostate-specific membrane antigen (PSMA) PET/CT for the detection of local disease within the prostat...

A Single-Center Evaluation of Extended Infusion Piperacillin/Tazobactam for Empiric Treatment in the Intensive Care Unit.

Piperacillin/tazobactam (PTZ) extended infusion (EI) is often used empirically in the intensive care unit (ICU). Gram-negative (GN) organisms with PT...

Fusion of multiple segmentations of medical images using OVASSION and Deep Learning methods: Application to CT-Scans for tumoral kidney.

Nephroblastoma is the most common kidney tumour in children. Its diagnosis is based on imagery. In the SAIAD project, we have designed a platform for ...

Simulated clinical deployment of fully automatic deep learning for clinical prostate MRI assessment.

OBJECTIVES: To simulate clinical deployment, evaluate performance, and establish quality assurance of a deep learning algorithm (U-Net) for detection,...

Machine learning for predicting long-term kidney allograft survival: a scoping review.

Supervised machine learning (ML) is a class of algorithms that "learn" from existing input-output pairs, which is gaining popularity in pattern recogn...

Unplanned Conversion from Minimally Invasive to Open Kidney Surgery: The Impact of Robotics.

Unplanned conversion from minimally invasive surgery (MIS) to open surgery is a significant challenge, although the frequency of conversion for robot...

Artificial intelligence assistance significantly improves Gleason grading of prostate biopsies by pathologists.

The Gleason score is the most important prognostic marker for prostate cancer patients, but it suffers from significant observer variability. Artifici...

Multicenter Multireader Evaluation of an Artificial Intelligence-Based Attention Mapping System for the Detection of Prostate Cancer With Multiparametric MRI.

The purpose of this study was to evaluate in a multicenter dataset the performance of an artificial intelligence (AI) detection system with attention...

Dr. Answer AI for prostate cancer: Clinical outcome prediction model and service.

OBJECTIVES: The importance of clinical outcome prediction models using artificial intelligence (AI) is being emphasized owing to the increasing necess...

Development and validation of an explainable artificial intelligence-based decision-supporting tool for prostate biopsy.

OBJECTIVES: To develop and validate a risk calculator for prostate cancer (PCa) and clinically significant PCa (csPCa) using explainable artificial in...

Hybrid Alchemical Free Energy/Machine-Learning Methodology for the Computation of Hydration Free Energies.

A methodology that combines alchemical free energy calculations (FEP) with machine learning (ML) has been developed to compute accurate absolute hydra...

Machine Learning Model for Risk Prediction of Community-Acquired Acute Kidney Injury Hospitalization From Electronic Health Records: Development and Validation Study.

BACKGROUND: Community-acquired acute kidney injury (CA-AKI)-associated hospitalizations impose significant health care needs and contribute to in-hosp...

PSA-based machine learning model improves prostate cancer risk stratification in a screening population.

CONTEXT: The majority of prostate cancer diagnoses are facilitated by testing serum Prostate Specific Antigen (PSA) levels. Despite this, there are li...

Digital application developed to evaluate functional results following robot-assisted radical prostatectomy: App for prostate cancer.

INTRODUCTION: Mobile applications ("apps") developed for smartphones and tablets are increasingly used in healthcare, allowing remote patient support ...

Internal and External Validation of a Machine Learning Risk Score for Acute Kidney Injury.

IMPORTANCE: Acute kidney injury (AKI) is associated with increased morbidity and mortality in hospitalized patients. Current methods to identify patie...

Using deep learning to predict beam-tunable Pareto optimal dose distribution for intensity-modulated radiation therapy.

PURPOSE: Many researchers have developed deep learning models for predicting clinical dose distributions and Pareto optimal dose distributions. Models...

The Use of Cumulative Sum Analysis to Derive Institutional and Surgeon-Specific Learning Curves for Robot-Assisted Radical Prostatectomy.

The cumulative sum (CUSUM) approach has been adopted to evaluate surgical competence in various contexts. The CUSUM method comprises sequential monit...