Pathology

Deep learning-based prediction of gene expression from histopathology identifies NR5A1 as a candidate biomarker and druggable target in high-grade serous ovarian carcinoma.

BACKGROUND: High-grade serous ovarian cancer (HGSOC) is the most lethal ovarian cancer subtype, responsible for ~ 70% of ovarian cancer-related deaths and marked by late-stage diagnosis and frequent platinum resistance. Although transcriptomic profiling enables molecular stratification and prediction of therapeutic response; routine clinical use of this approach is limited by cost and logistical c...

FSCL-BC: Federated supervised contrastive learning for breast cancer diagnosis with high sensitivity.

BACKGROUND AND OBJECTIVE: Accurate diagnosis of breast cancer in dense breasts requires expert radiologists to examine multiple ultrasound images per patient. This diagnosis procedure is tedious, time-consuming, and prone to misdiagnosis due to human fatigue. AI-aided diagnosis systems can help alleviate this burden. However, vast amounts of data from multiple hospitals, diverse patient demographi...

MicNet: integrating spatially resolved transcriptomes and pathology images by contrastive deep neural network.

Recent breakthroughs in spatially resolved transcriptomic technologies have enabled molecular characterization of cells while preserving spatial and m...

Wavelet Spectrum in a Multi-Channel Network May Reduce Biopsy Rates on Diagnosis of Breast Tumors with BI-RADS Category 4a or Higher.

OBJECTIVES: BI-RADS 4a+ breast tumors have a high rate of unnecessary biopsies due to ambiguous diagnostic features. This study aims to develop and ev...

Diagnostic Performance of Contemporary Large Language Models on Free-Text Histopathologic Descriptions in Oral and Maxillofacial Pathology.

PURPOSE: To benchmark the diagnostic accuracy and inter-model agreement of contemporary large language models (LLMs) on text-only histopathologic narr...

Identification of diagnostic and prognostic hub genes in osteoarthritis: an integrated bioinformatics study.

BACKGROUND: Osteoarthritis (OA) is a heterogeneous whole-joint disease and a leading cause of pain and disability worldwide. Synovial inflammation pla...

Deep Learning Based Framework for Detection and Classification of Leukemia Using Microscopic Images.

Excessive proliferation of white blood cells (WBCs) in the bone marrow leads to a type of blood cancer known as leukemia. This blood cancer impairs th...

TRPV1, Endocannabinoid, and Opioid Systems in Analgesia: Molecular Mechanisms and Drug Development Strategies.

Pain modulation relies on complex molecular interactions among ion channels, G protein-coupled receptors, and intracellular signaling cascades. The Tr...

Slow-wave-modulated high-frequency oscillations reveal early network abnormalities in pre-pathological 5XFAD mice.

Alzheimer's disease (AD) is characterized by progressive disruption of large-scale neural networks, leading to abnormal brain oscillatory activity, ye...

Reviving formalin-fixed, paraffin embedded (FFPE) tissues for on-slide and multiscale correlative microscopy.

Correlative microscopy integrates complementary imaging modalities to enable structural analysis of biological samples across multiple length scales. ...

Label-free classification of breast cancer subtypes in ex vivo human tissues using Raman spectroscopy and machine learning.

Breast conserving surgery (BCS) aims to excise breast tumors whilst preserving breast-related quality of life, but is complicated by the challenge of ...

Computational pathology model to predict recurrence-free survival in NMPUC patients on BCG-therapy.

Urothelial carcinoma, predominantly appearing as non-muscle-invasive papillary urothelial carcinoma (NMIPUC), exhibits wide clinical variability. Accu...

A machine learning model integrating two-dimensional ultrasound radiomics and clinical parameters for differentiating membranous nephropathy from IgA nephropathy.

BACKGROUND: Membranous nephropathy (MN) and IgA nephropathy (IgAN) are the two most common primary glomerular diseases in China, with distinct pathoph...

[Research progress in diagnostic key points of pediatric pathological myopia].

Pathological myopia has become one of the leading causes of irreversible blinding eye disease in China, yet its early diagnosis, especially in childre...

Transcriptomic analysis identifies novel ferroptosis-related biomarkers and therapeutic targets in pulmonary arterial hypertension.

BACKGROUND: Ferroptosis plays a significant role in pulmonary arterial hypertension (PAH), although its underlying mechanisms and key pathogenic genes...

Integrative single-cell and spatial transcriptomics with machine learning identify a Luminal-inflam malignant program and reveal an RPN1-PERK UPR vulnerability in triple-negative breast cancer.

Triple-negative breast cancer is marked by extensive cellular heterogeneity and limited availability of actionable targeted treatments, which contribu...

Cellular immunology data enable clinical severity prediction via supervised machine learning.

High-dimensional flow cytometry provides rich immunological data for examining immune responses and their relationships with disease pathology, but it...

Exploring artificial intelligence in point-of-care and standard breast ultrasound: a paired reader study.

BackgroundBreast cancer diagnoses are limited in low- and middle-income settings due to lack of medical resources. In these settings, point-of-care ul...

Diagnostic accuracy of an artificial intelligence-based breast ultrasound tool in pregnant and lactating patients.

OBJECTIVES: To assess the diagnostic performance of an artificial intelligence (AI)-based decision support tool for breast ultrasound in pregnant and ...

Identifying PLAU as a shared pathogenic gene in type 2 diabetes and bladder urothelial carcinoma through integrated transcriptomic analysis and machine learning for diagnostic and therapeutic value.

Type 2 diabetes mellitus (T2DM) and bladder urothelial carcinoma (BLCA) are two kinds of diseases that seriously threaten human health. Their pathogen...