Urology

ProsMAE: Multi-Source MAE Pretraining for ISUP Grade Classification

Whole slide images (WSIs) provide rich diagnostic information for computational pathology, but their gigapixel scale, stain variation, scanner differences, tissue artifacts, and limited expert annotation make robust model training challenging. This paper presents a multi-source Masked Autoencoder (MAE) framework, named ProsMAE, for histopathology representation learning. Tiles from Prostate cANcer...

Mechanistically informed adaptive dosing for cancer immunotherapy using AI-guided decision making

Optimizing dose and schedule remains a central challenge in oncology drug development, particularly for immunotherapies where fixed dosing regimens often fail to account for patient specific heterogeneity in tumor-immune dynamics. Here, we present a hybrid quantitative systems pharmacology-reinforcement learning-Monte Carlo Tree Search (QSP-RL-MCTS) framework for personalized immunotherapy dosing ...

Compass: Prostate Cancer Detection Needs Multi-View Context

Artificial intelligence (AI) analysis of micro-ultrasound ($μ$US) has shown promise for prostate cancer (PCa) detection. However, most existing AI met...

FORGE: Towards Functional Tool-Use Generalization via Keypoint Trajectory Reasoning

While humans readily repurpose a book, a stone, or a shoe to drive a nail, robots trained on specific tools fail to transfer the same function to nove...

KOAL: Knowledge-Driven Prostate Cancer Grading with Ordinal-Aware Learning

Non-invasive prediction of Gleason Grade Group (GGG) in prostate cancer using multiparametric MRI (mpMRI) is clinically vital for reducing unnecessary...

Feature Selection with Quantum Annealing for Biomedical Machine Learning Applications

Feature selection is a commonly used method in biomedical artificial intelligence and machine learning to identify a subset of high-quality variables ...

RenalTransLSTM: Multi-Horizon Prediction of Acute Kidney Injury in ICU Patients using a Hybrid LSTM-Transformer Architecture

Objective: Acute kidney injury (AKI) affects a large proportion of patients in the intensive care unit (ICU) and is a major contributor to morbidity, ...

HCSU: A Dataset and Benchmark for Fine-Grained Historical Calligraphy Style Understanding

Automated fine-grained perception of calligraphy styles--a task vital to cultural heritage preservation--remains a critical challenge for Large Vision...

Developing an OMOP-Standardized Prostate Cancer Database and Improving Data Quality Using NLP and PSA-Based Algorithms

Objective: To develop and evaluate an Observational Medical Outcomes Partnership (OMOP) standardized prostate cancer database from the University of T...

Zero-Shot Metabolite Prediction from Gene Expression via Physics-Informed Graph Neural Networks

Predicting metabolite concentrations from gene expression is instrumental for linking regulatory programs to metabolic phenotypes. Prior approaches re...

Population-Scale Segmentation of Penile Tissue in DIXON MRI using Deep Learning for Quantitative Phenotyping in Male Reproductive Health

Penile measurement is clinically relevant across male reproductive and urogenital health, including conditions such as micropenis, congenital and endo...

Distilling Temporal Coherence into 2D Networks for Transrectal Ultrasound Prostate Video Segmentation

Real-time video segmentation of the prostate in Transrectal Ultrasound (TRUS) is essential for image-guided interventions. While conventional 2D metho...

Learning Where to Look: A Reinforcement Learning Framework for Robust Micro-Ultrasound Prostate Cancer Detection

Micro-ultrasound ($μ$US) is a new, emerging, and promising imaging modality for prostate cancer (PCa) detection, but accurate identification of suspic...

PHO-Agents: A Large Language Model Powered Multi-Agent System for Predicting Health Outcomes

Objective: Predicting health outcomes from electronic health records (EHRs) is challenging because traditional models rely on structured data and ofte...

A multi-architecture study of specificity refinement and false-positive mechanism analysis in prostate MRI

Objectives: To characterize residual false positives in prostate MRI detection, and to evaluate a lightweight post-hoc refinement head for case-level ...

A Visually Interpretable Histopathology-Based Immune Model Predicts T-effector Biology and Response to Immune checkpoint inhibition in Clear Cell Renal Cell Carcinoma Clinical Trial and Contemporary Real-World Datasets

Immune checkpoint inhibitors (ICI) are central to the treatment of metastatic clear cell renal cell carcinoma (ccRCC), yet only a subset of patients d...

Development and Validation of Machine Learning Models for Predicting Initiation of Emergency Dialysis in Advanced Chronic Kidney Disease

BackgroundInitiation of emergency dialysis, often requiring temporary catheter owing to unprepared definitive vascular access, is associated with infe...

Automated Segmentation of Prostatic Gold Fiducial Markers for MR-Only Radiotherapy Planning Using Multi-Modal Consensus Deep Learning

Purpose: To develop and evaluate a multi-model consensus deep learning approach for automated gold fiducial marker (FM) segmentation in T1-weighted pr...

Concept Alignment Contrast and Long-Short Prompt Memory for Test-Time Adaptation of SAM3 in Medical Image Segmentation

Concept segmentation models like Segment Anything Model 3 (SAM3) show strong generalization on natural images, yet their performance degrades in medic...

Multi-cancer detection using a computationally efficient CNN with transfer learning

This study introduces a computationally efficient convolutional neural network (CNN) architecture enhanced with transfer learning for multi-cancer det...