Pathology

AI-discovered cellular morphometric biomarkers in needle biopsy of prostate cancer predict neoadjuvant androgen deprivation therapy response and enable therapeutic targeting of mTOR in androgen deprivation therapy-resistant tumors.

It is imperative to identify patients with prostate cancer (PCa) who will not benefit from androgen ...

Assessment of a Deep Learning Model Trained on Permanent Pathology for the Classification of Squamous Cell Carcinoma in Mohs Frozen Sections: Lessons Learned.

Bioinformatics and machine learning identify ITIH4 and ZC3H13 as novel mRNA biomarkers for major depressive disorder that promote microglial M1 polarization.

UNLABELLED: Major depressive disorder (MDD), a prevalent mental illness, currently lacks reliable bi...

2D Multimodal Image Collection for Fluorescence Prediction from Transmitted Light Microscopy.

We present the Light My Cells Database, a large-scale open-access collection comprising 2,574 acquis...

Machine learning vs. radiomics for discriminating atypical cartilaginous tumors from benign enchondromas on MRI.

BACKGROUND: Enchondromas (EC) present cartilaginous tumors that are difficult to differentiate from ...

Artificial Intelligence-Driven Segmentation of Three Oral Diseases: Enabling Precision Diagnosis and Decision Support.

INTRODUCTION: The advancement of AI-assisted oral disease diagnosis critically relies on the availab...

Integrated single-cell and bulk transcriptomic analysis identifies epithelial cell-related biomarkers and immune subtypes in focal segmental glomerulosclerosis.

BACKGROUND: Focal segmental glomerulosclerosis (FSGS) is a major cause of nephrotic syndrome and chr...

CT-Based Automated Segmentation and Recurrence Prediction in Chronic Subdural Hematoma: A Dual-Label Multicenter Study.

Chronic subdural hematoma (CSDH) frequently recurs after burr-hole surgery, yet most prior imaging s...

A deep learning pipeline for mapping in situ network-level neurovascular coupling in multi-photon fluorescence microscopy.

Functional hyperemia is a well-established hallmark of healthy brain function, whereby local brain b...

Imaging-Based Prediction of Key Breast Cancer Biomarkers Using Deep Learning on Digital Breast Tomosynthesis.

OBJECTIVE: To evaluate the feasibility of using deep learning models applied to digital breast tomos...

Deep learning reconstruction enables accelerated T2-weighted MRI for rectal cancer staging: a prospective study of diagnostic consistency across NEX value reduction.

OBJECTIVES: To evaluate the image quality, interpretation consistency, and scanning efficiency of de...

PNET-PRISM: a multicenter-validated radiomics nomogram for noninvasive grading of pancreatic neuroendocrine tumors.

BACKGROUND: Accurate preoperative grading of pancreatic neuroendocrine tumors (PNETs) is essential f...

Negligible impact of perifissural nodules in an AI-first reader workflow from UK lung screening trial.

OBJECTIVE: To evaluate the effect of perifissural nodules (PFNs) on radiologist workload within an A...

A deep learning approach for the diagnosis and recurrence prediction of OKC.

Odontogenic Keratocyst (OKC) is a benign jaw tumor characterized by a high recurrence rate. However,...

Statistical evaluation of fresh properties of self-compacting concrete incorporating construction and industrial waste: a sustainable approach.

This study investigates the fresh properties of self-compacting concrete (SCC) developed using recyc...

Digital pathology platforms with integrated AI algorithms: a structured landscape analysis and recommendations for clinical implementation.

Pathology is undergoing a fundamental change as slide-based diagnostics transition toward digital wo...

FTO-CHRM3 axis regulates multiple myeloma progression: a machine learning-based identification.

BACKGROUND: Fat Mass and Obesity-Associated (FTO) is linked to multiple myeloma (MM) progression, bu...

Exploring Deep Learning Models for Small Histopathology Datasets: Segmentation and Classification of Glomerular Crescent Lesions with Ablation, Interpretability, and Calibration Analyses.

Glomerular crescent lesions are critical indicators of severe kidney injury and are closely associat...

Integrated single-cell and spatial mapping coupled with machine learning unveils core stemness landscapes and regulatory drivers in triple-negative breast cancer.

OBJECTIVE: Triple-negative breast cancer (TNBC) exhibits pronounced intratumoral heterogeneity, and ...

High-fidelity "top-down" DLP bioprinting of multi-material soft tissue constructs enabled by computer vision-based layer control.

Bioprinting continues to redefine the frontiers of regenerative medicine by enabling the fabrication...

Integrative machine learning analysis suggests novel molecular targets for liver cancer diagnosis and therapy.

BACKGROUND: Hepatocellular carcinoma (HCC) is a critical condition characterized by unchecked cellul...