Urology

Development and validation of a personalized web-based calculator of aggressive recurrence after surgery for early-stage hepatocellular carcinoma by machine learning.

BACKGROUND: Aggressive recurrence (AR) is an important factor affecting prognosis after surgery for hepatocellular carcinoma (HCC). This study aimed to establish and evaluate a visual calculator to predict AR using by machine learning (ML) model. METHODS: Patients diagnosed with HCC at an early stage were reviewed. The prediction ability of each model was evaluated using accuracy, sensitivity, spe...

Early prediction of response to ADT plus ARPIs in mHSPC using interpretable machine learning on PSMA PET/CT: a real-world study.

BACKGROUND: Reliable tools for early prediction of treatment response to androgen deprivation therapy (ADT) plus novel androgen receptor pathway inhibitors (ARPIs) in metastatic hormone-sensitive prostate cancer (mHSPC) remain lacking. This study aimed to develop and validate an interpretable machine learning model integrating [⁶⁸Ga]Ga-PSMA PET/CT-derived imaging features to predict response befor...

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 critical for guiding lymph node dissection. Current no...

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 model can enhance image quality of diffusion weight...

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 provide estimates of diagnostic accuracy of AI assista...

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 and classification of complicated cystic renal mass...

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 that are difficult to forecast, particularly in p...

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, some of which can spread and migrate to other tis...

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

RATIONALE AND OBJECTIVES: Androgen deprivation therapy (ADT) efficacy exhibits significant interindividual heterogeneity in advanced prostate cancer (...

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 diagnosis. While recent artificial intelligence-b...

A Comparative, Multiobserver Analysis of Nodal Contouring Methods in Pelvic Online Cone Beam-Based Adaptive Radiation Therapy.

PURPOSE: In online cone beam computed tomography (CBCT)-based adaptive radiation therapy (ART), nodal recontouring ensures sufficient nodal coverage b...

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 chronic kidney disease and an antecedent cause of adult-...

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 better energy discrimination and higher spatial r...

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 hypothesized to be associated with wall thrombus bu...

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 disease (DKD) and end-stage kidney disease (ESKD) are n...

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, assessing invasion depth-distinguishing between superfi...

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 probing renal perfusion. However, traditional method...

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-based reconstruction (DLR2) with a metal artifact re...

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

KEY POINTS: Artificial intelligence models effectively generalized across studies and animal models and reduced translational gaps when applied to hum...