Urology

Lymph Node Invasion Prediction in Prostate Cancer: A Comparative Machine-Learning Study.

BACKGROUND: Accurate preoperative prediction of lymph node invasion (LNI) in prostate cancer is crit...

Comparing prostate diffusion weighted images reconstructed with a commercial deep-learning product to a deep learning phase corrected model at 1.5 T.

PURPOSE: To determine whether a new deep learning (DL) based phase corrected (DLPC) reconstruction m...

Editorial for "Development and Deployment of a Machine Learning Model to Triage the Use of Prostate MRI (ProMT-ML) in Patients With Suspected Prostate Cancer".

AI-aided diagnostic performance for prostate MRI: systematic review and meta-analysis.

BACKGROUND: AI is increasingly integrated within prostate cancer diagnosis pathway. PURPOSE: To prov...

Machine learning pipeline for automated segmentation and classification of complicated cystic renal masses on MRI: comparison with radiologists' assessments.

PURPOSE: To develop and validate a machine learning (ML)-based pipeline for automated segmentation a...

Explainable machine learning-based prediction of psoriatic arthritis flares using heterogenous real-world data for personalised patient care.

Psoriatic arthritis (PsA) is a chronic inflammatory disease characterised by unpredictable flare-ups...

Molecular targeted therapies, omics, and AI based theranostics approaches for the treatment of prostate cancer.

Cancer is a disease that begins with genetic and epigenetic alterations occurring in specific cells,...

mpMRI-based interpretable machine learning model for predicting castration-resistant prostate cancer risk.

RATIONALE AND OBJECTIVES: Androgen deprivation therapy (ADT) efficacy exhibits significant interindi...

A systematic analysis of the impact of data variation on AI-based histopathological grading of prostate cancer.

The histopathological evaluation of biopsies by human experts is a gold standard in clinical disease...

Molecular pathways of kidney development and their applications to clinical research.

Congenital anomalies of the kidney and urinary tract (CAKUT) are the major cause of childhood chroni...

Accuracy of Photon Dose Calculation on Photon-Counting Computed Tomography-A Comparison Study Based on Virtual Monoenergetic and Electron Density (Rho) Images for Pancreatic Cases.

PURPOSE: Photon-counting computed tomography (PCCT) offers versatile anatomic information because of...

Unsupervised machine learning for identifying morphological phenotypes in abdominal aortic aneurysms using fully automated volume-segmented imaging: a multicentre cohort study.

AIMS: Thrombo- and microembolic complications following abdominal aortic aneurysm (AAA) repair are h...

Diverse combination of factors associated with the development of diabetic kidney disease among data-driven diabetes subtypes: analysis of the J-DREAMS registry.

AIMS/HYPOTHESIS: Available methods for predicting the onset and progression of diabetic kidney disea...

White Light, Magnifying Endoscopy, Endocytoscopy, and Artificial Intelligence in Diagnosis of Early Colorectal Cancer: A Comparative Study.

OBJECTIVES: Early detection of colorectal cancer is critical for improving prognosis. However, asses...

Deep learning-based perfusion quantification and large vessel exclusion for renal multi-TI arterial spin labelling MRI.

The multi-TI flow-sensitive alternating inversion recovery sequence is a common ASL technique for pr...

Diagnostic value of a second-generation super-resolution deep learning-based reconstruction combined with a metal artifact reduction algorithm for pelvic CT.

OBJECTIVE: To evaluate the impact of combining a second-generation super-resolution deep learning-ba...

Streamlining the Histopathologic Workflow in Diabetic Kidney Disease with Artificial Intelligence.

KEY POINTS: Artificial intelligence models effectively generalized across studies and animal models ...

Intraoperative assessment of surgical margins during radical prostatectomy: advances and challenges.

PURPOSE OF REVIEW: Detection of positive surgical margins during radical prostatectomy is critical t...

Self-Supervised Noise Adaptive MRI Denoising via Repetition to Repetition (Rep2Rep) Learning.

PURPOSE: This work proposes a novel self-supervised noise-adaptive image denoising framework, called...

Artificial intelligence in nephrology: predicting CKD progression and personalizing treatment.

Chronic kidney disease (CKD) represents a major and expanding global health challenge, with prevalen...

AI-powered chronic kidney disease detection integrating TabNet and LSTM for precision diagnosis.

Chronic kidney disease (CKD) is a leading cause of morbidity and mortality worldwide, with early det...