Urology

Deep Learning Enables Automated Segmentation and Quantification of Ultrastructure from Transmission Electron Microscopy Images

The widths of kidney glomerular basement membrane (GBM) and podocyte foot processes (FP) are essential ultrastructural markers for assessing kidney function and diagnosing glomerular disease. FP widening reflects podocyte injury, whereas GBM thickening is characteristic of conditions such as diabetic nephropathy and Alport syndrome. Current measurement practices depend on manual tracing and expert...

DeepPathway: Predicting Pathway Expression from Histopathology Images

Spatial transcriptomics (ST) technologies provide spatially resolved gene expression along with image data, allowing the integrative analysis of complex tissue microenvironments. Despite their potential, the widespread adoption of ST remains limited due to high costs, and methodological challenges in data acquisition. Thus, there have been recent efforts to develop deep learning methods capable of...

SAM-based Automatic Workflow for Histology Cyst Segmentation in Autosomal Dominant Polycystic Kidney Disease

Autosomal Dominant Polycystic Kidney Disease (ADPKD) is a genetic disorder characterized by the development of numerous cysts in the kidneys, ultimate...

A Minimal Plasma Proteome-Based Biomarker Panel for Accurate Prostate Cancer Diagnosis

Early and accurate diagnosis of prostate cancer (PRC) remains a major clinical challenge, particularly with existing biomarker panels relying on invas...

ATHENA: A deep learning–based AI for functional prediction of genomic mutations and synergistic vulnerabilities in prostate cancer

Identifying functional mutations that drive therapy resistance remains a major challenge in prostate cancer. Large-scale sequencing often produces ext...

A memory-driven reinforcement learning model of phenotypic adaptation for anticipating therapeutic resistance in prostate cancer

While contemporary cancer treatment strategies have significantly prolonged the lives of patients, therapeutic resistance remains a predominant cause ...

cfOncoXpress: Tumor gene expression prediction from cell-free DNA whole-genome sequences

Cell-free DNA (cfDNA) fragments in the plasma capture cellular nucleosomal profiles since nucleosome-protected regions escape enzymatic degradation wh...

Multi-cohort, cross-species urinary proteomics reveals signatures of LRRK2 dysfunction in Parkinson’s disease

Pathogenic mutations in Leucine-rich repeat kinase 2 (LRRK2) are the predominant genetic cause of Parkinson’s disease (PD) and often increase kinase a...

A Multi-Modal Transfer Learning Framework to Reduce Health Disparities in Prostate Adenocarcinoma

Prostate cancer is the second most common cancer in men across the United States, of which prostate adenocarcinoma (PRAD) is the most common subtype. ...

Machine-learning-based determination of sex-related bladder cancer biomarkers

Bladder cancer exhibits sex-specific behavior, occurring more frequently in males but progressing to advanced stages more commonly in females. The act...

Using GPT-4 to Automate the Generation of Lay Summaries for Cancer Publications

Cancer research literature is often riddled with technical jargon that is not digestible to the average person. Individuals interested in research stu...

MOTLAB: A Weighted Multi-Omics Transfer Learning Approach to Mitigate Breast Cancer Racial Disparities

Breast cancer (BC) is a leading cause of cancer death among women in United States. Previous studies have indicated that Black American women have dis...

Asymmetric Cross-Reactivity of Nuclear Receptors Reveals an Evolutionary Buffer Between Estrogen and Androgen Signaling

A comprehensive all-by-all receptor ligand affinity screen using Boltz-2, a deep learning framework for protein-ligand interaction prediction, reveals...

BCL-XL Dependence is a Subtype Agnostic Actionable Feature of Difficult-to-Treat Kidney Cancers

The BCL-XL anti-apoptotic protein is a clear cell Renal Cell Carcinoma (ccRCC) dependency; however, the mechanism of this dependence and its relevance...

lncAPNet enables the deciphering of lncRNA–mRNA connections in patient transcriptomic data

Long non-coding RNAs (lncRNAs) regulate gene expression through chromatin remodeling, transcriptional control, and post-transcriptional modulation, in...

Machine learning prediction algorithms for 2- , 5- and 10-year risk of Alzheimer’s, Parkinson’s and dementia at age 65: a study using medical records from France and the UK General Practitioners

Leveraging machine learning on electronic health records offers a promising method for early identification of individuals at risk for dementia and ne...

Deep Learning Identified Extra-Prostatic Extension and Seminal Vesicle Invasion as an MRI Biomarker for Prostate Cancer Outcomes

Current risk stratification methods for localized prostate cancer (PCa) are reliant on clinical and pathological variables that do not easily account ...

Predicting ADC Map Quality from T2-Weighted MRI: A Deep Learning Approach for Early Quality Assessment to Assist Point-of-Care

Poor quality prostate MRI images, especially ADC maps, can lead to missed lesions and unnecessary repeat scans. To address this issue, we aimed to dev...

ORAKLE: Optimal Risk prediction for mAke30 in patients with acute Kidney injury using deep Learning

Major Adverse Kidney Events within 30 days (MAKE30) is an important patient-centered outcome for assessing the impact of acute kidney injury (AKI). Th...

Few-Shot Learning for Prostate Cancer Detection on MRI: Comparative Analysis with Radiologists’ Performance

Deep-learning models for prostate cancer detection often require large datasets, which can be challenging to obtain and may lead to domain shift issue...