Pathology

Automated Detection and Classification of Radiology Report Discrepancies Using NLP: A Tool for Resident Education and Quality Assurance.

PURPOSE: The aim of this study was to develop and evaluate a natural language processing (NLP) system that automatically detects and classifies discrepancies between preliminary and final radiology reports, with the goal of enhancing resident education through structured feedback. METHODS: A total of 889 deidentified lumbar spine MRI reports (768 with revisions) from December 2023 to March 2024 we...

Towards generalizable pathology reports via a multimodal LLM with the multicenter in-context learning.

Pathology report generation has received increasing attention in recent years. However, existing pathology report generation methods still face two main limitations: (1) these methods utilize image-report datasets where some report contents are irrelevant to the given whole slide image (WSI), making it unreliable to train an AI model to generate such content; (2) existing methods trained on data f...

LCPBert: ProtBERT-based early-stage lung cancer prediction from T cell receptor beta sequences.

Early detection of lung cancer remains challenging due to limitations of current methods. We developed LCPBert, a deep learning framework leveraging p...

Ultrasonographic Evaluation of Pediatric Thyroid Nodules: Adult Risk Stratification Systems, 2021 K-TIRADS Revision, and Future Refinements.

Although pediatric thyroid cancer is rare, it has characteristics distinct from those of adult thyroid cancer. Thyroid nodules in children present a h...

Bridging electron microscopy and materials analysis with an autonomous agentic platform.

Electron microscopy (EM) reveals atomic-scale structures that underpin catalysis, energy storage, and semiconductor reliability, yet current workflows...

Artificial Intelligence-Based Exosome Analysis for Improving Diagnostic Performance of Breast Lesions on Ultrasound: Protocol of a Prospective, Multicenter Cohort Study.

PURPOSE: Exosome-surface enhanced Raman spectroscopy-artificial intelligence platform (exosome-SERS-AI) is an innovative liquid biopsy method that acq...

CRISPR-Cas system: recent advancements in prompt diagnosis of high-risk HPV genotypes in cervical cancer.

INTRODUCTION: The CRISPR/Cas system has emerged as a highly versatile platform for diagnosing infectious diseases, particularly viral pathogens. Human...

Deep learning-based image super-resolution in microscopy: Why more pixels do not imply higher resolving ability?

Deep learning-based image super-resolution is a popular topic in computer vision and artificial intelligence (AI)-based imaging. A survey of literatur...

Factors Influencing Universal Coverage of AI-Assisted Cervical Cancer Screening: Qualitative Study Based on the Macro Model of Health System.

BACKGROUND: Improving screening coverage is a central goal of the global strategy to eliminate cervical cancer. In resource-constrained settings, insu...

Evolution of the Diagnostic Paradigm for Giant Cell Arteritis: From Histopathology to Multi-Modal Imaging Integration Running title: GCA: Histology to Imaging.

Giant cell arteritis (GCA) is a systemic vasculitis that predominantly affects mediumand large-sized arteries. Delayed diagnosis may result in irrever...

An end-to-end generalizable deep learning framework to comprehensively analyze transcriptional regulation.

Genome annotation currently requires performing dozens of molecular assays in hundreds of cell and tissue samples, an expensive endeavor which is impr...

Oxidative stress reprograms benign prostatic hyperplasia microenvironments: insights from integrative multi-omics and machine learning.

BACKGROUND: Oxidative stress (OS) is increasingly implicated in benign prostatic hyperplasia (BPH), yet the underlying cellular programs remain unclea...

Enhancing AI's ability to interpret histological images with prompt engineering: An evaluation of GPT-4o performance.

This study examines the effect of various prompting strategies on ChatGPT's ability to interpret histological images across different tissue types and...

Deep learning model for pathological invasiveness prediction using smartphone-based surgical resection images in clinical stage IA lung adenocarcinoma (SuRImage): a prospective, multicentric, diagnostic study.

BACKGROUND: In clinical stage IA lung adenocarcinoma (LUAD), rapid and accurate intraoperative diagnosis is crucial to decide whether to perform segme...

Higher Diagnostic Accuracy of an AI Model for Colposcopy Compared With Conventional and Digital Colposcopic Evaluation.

OBJECTIVE: Colposcopy involves subjective visual assessment of cervical features that may indicate cervical dysplasia. Pattern recognition during colp...

Deep Learning Empowered Microstructure Codebook: New Paradigm for Multi-Parameter Tissue Characterization Estimation.

Diffusion MRI (dMRI) enables the examination of microstructural profiles and tissue changes using specific microstructural modeling, but it requires l...

Artificial intelligence in nongynecologic cytology: A systematic review of current research and commercial tools.

BACKGROUND: Nongynecologic (non-GYN) cytology plays an important role in cellular and molecular cancer diagnosis, although its use is limited by varia...

Multicentre Evaluation of an AI-Assisted Urine Test for Clinically Significant Prostate Cancer in Men Undergoing Initial Biopsy.

The Extracellular Vesicles Gene-based Prostate Score (EGPS), powered by DeepSeek, is an artificial intelligence (AI) diagnostic tool that enhances the...

A deep learning model for histopathological diagnosis of actinic keratosis: a diagnostic case control accuracy study.

BACKGROUND: Actinic keratosis (AK) is a precancerous skin lesion with the potential to progress into squamous cell carcinoma (SCC), with an overall pr...

Usefulness of Artificial Intelligence for Surgical Support in Robot-assisted Distal Pancreatectomy: A Preliminary Case Report.

BACKGROUND/AIM: The incidence of postoperative complications in minimally-invasive surgery for pancreatic disease remains a concern. The application o...