Pathology

A Review of the Use of Artificial Intelligence in Ophthalmology Imaging: Approximation to Ocular Histopathology.

Ophthalmic imaging has advanced to a level at which it can closely approximate key histopathological features of certain ocular tissues, changing the way ocular disease is screened for, diagnosed, and monitored. Modalities such as optical coherence tomography (OCT), anterior segment OCT (AS-OCT), OCT angiography (OCTA), and in vivo confocal microscopy (IVCM) capture tissue architecture with high-r...

Integrative Multi-Omics Analysis Identifies Thrombosis-Associated Molecular Features Linked to Germline Susceptibility and Immune Cell Communication in Gastric Cancer.

Emerging evidence indicates that coagulation-related molecular programs are associated with thrombosis, tumor progression, and molecular dysregulation in gastric cancer (GC). However, thrombosis-associated molecular features in GC and their potential links to inherited susceptibility remain insufficiently understood. Integrated analyses of transcriptomic data from The Cancer Genome Atlas (TCGA) an...

Applications of Deep Learning in Endocrine Neoplasms.

Machine learning methods have been growing in prominence across all areas of medicine. In pathology, recent advances in deep learning (DL) have enable...

Diagnostic performance of artificial intelligence models trained on scattered single-cell images is not preserved for hyperchromatic crowded cell groups in cervical cytology.

BACKGROUND: Deep learning has shown promising performance in cervical cytology; however, many studies have relied on presegmented single-cell images r...

Natural language processing to develop a standardized lexicon for precision medicine in oncology.

Precision medicine terminology is increasingly used across clinical, laboratory, payer, regulatory, and policy settings; however, distinct terminology...

Assessment of atypical glandular cell interpretation in Pap tests using the Hologic Genius Digital Diagnostics System.

Atypical glandular cells (AGC) are a diagnostic challenge. The aim of this study was to evaluate the efficacy and diagnostic performance of AGC detect...

Cross-tissue immune profiling of APOE ε4 reveals early dysregulation in Alzheimer's disease.

INTRODUCTION: Apolipoprotein E (APOE) ε4 is the strongest genetic risk factor for late-onset Alzheimer's disease (AD), but its contribution to disease...

Probing polymer nanostructures with super-resolution fluorescence microscopy.

Super-resolution fluorescence microscopy (SRM) has emerged as a powerful tool for polymer characterization, providing nanometer-scale spatial resoluti...

Heparan Sulfate Proteoglycans: Master Regulators of Cellular Signaling, Tissue Development, and Neural Function.

This narrative review examines the essential roles of heparan sulfate proteoglycans (HSPGs) in brain development, synaptic function, axonal guidance, ...

Artificial intelligence-assisted histopathological diagnosis of endocervical gastric-type adenocarcinoma: a multicenter model development and validation study.

Endocervical gastric-type adenocarcinoma (GAS) is one of the most aggressive subtypes of cervical cancer and is frequently underdiagnosed due to morph...

Benchmarking Vision Encoders for Image Classification in Ophthalmology.

Foundation vision encoders are rapidly emerging as the standard for retinal artificial intelligence. Yet, ophthalmology still lacks a comprehensive be...

Non-invasive differentiation of diffuse midline glioma and midline glioblastoma using DCE-MRI perfusion parameters and machine learning classification in pediatric and young adult patients.

PURPOSE: Diffuse midline glioma (DMG) and midline glioblastoma (mGBM) are aggressive WHO grade 4 tumors with comparable median survival of 12-18 month...

Silencing SLC52A2 promotes tertiary lymphoid structure formation and inhibits IL-17 pathway to ameliorate melanoma progression.

Tertiary lymphoid structure (TLS) correlates with improved prognosis in melanoma. The role of solute carrier family 52 member A2 (SLC52A2) in mediatin...

High-resolution 3D micro-CT reveals an additional muscle layer in esophageal atresia.

BACKGROUND: Esophageal atresia (EA) is a congenital malformation intrinsically associated with esophageal dysmotility. Its etiology is poorly understo...

'In silico labelling': Exploring the biological landscape at the nanoscale using intelligent multimodal optical microscopy.

Multimodal optical microscopy has recently converged with artificial intelligence (AI) to enable in silico labelling-the computational prediction of f...

Microscopy image segmentation using a fine-tuned machine learning model with limited training dataset.

Manual annotation of microscopic images of thin tissue sections remains time-consuming step limiting the throughput of diagnostic analysis. We present...

A Deep Learning Framework to Classify Oral Squamous Cell Carcinoma arising in Oral Submucous Fibrosis using Whole-slide Images.

OBJECTIVES: Oral submucous fibrosis (OSF) is a chronic and progressive potentially malignant disorder with an increased risk of transformation to oral...

From metabolite mapping to precision imaging: advances in in vivo MR spectroscopy of brain tumours.

Magnetic resonance spectroscopy (MRS) provides non-invasive in vivo assessment of brain tumour metabolism and complements conventional magnetic resona...

A novel convolution-transformer model for differentiating hypertrophic cardiomyopathy from Phenocopies using cardiac MRI.

BACKGROUND AND OBJECTIVES: Hypertrophic Cardiomyopathy (HCM) is the most prevalent inherited cardiomyopathy. Its left ventricular hypertrophy (LVH) ph...

Graph-Based Neural Network for Malignancy Detection in Breast Ultrasound Images using Medically Significant Features.

OBJECTIVE: Breast ultrasound imaging is widely used for the early detection of malignant breast lesions. Although deep learning models have shown stro...