Pathology

Co-repression of Yap1 and Sox9 Abrogates Established Cholangiocarcinoma by Eliminating Transcriptional Compensation.

BACKGROUND/AIMS: Intrahepatic cholangiocarcinoma (iCCA) represents an unmet clinical need due to its increasing incidence, aggressive biology, and limited treatment options. The extremely low-response rates to current systemic regimens and the emergence of adaptive resistance to targeted therapies underscore the urgent need for alternative therapeutic strategies. Given that the lineage-defining tr...

Computational models for predicting bone fracture healing: a review of modeling approaches, predictions, and emerging strategies.

BACKGROUND AND OBJECTIVE: The development of computational models for predicting bone fracture healing process holds strong potential to optimize therapeutic management in non-unions and delayed healing, reducing healthcare costs and disability-adjusted life years. The main goal of this study is to provide a thoroughly comparative analysis to computational models already proposed to predict fractu...

Label-free pathological subtyping of non-small cell lung cancer using deep classification and virtual immunohistochemical staining.

The differentiation between pathological subtypes of non-small cell lung cancer (NSCLC) is an essential step in guiding treatment options and prognosi...

Construction of an interpretable multimodal image model for differentiating T1-stage nasopharyngeal carcinoma from benign hyperplasia.

BACKGROUND AND OBJECTIVE: Differentiating T1-stage nasopharyngeal carcinoma (NPC) from benign hyperplasia (BH) is challenging. This study aims to cons...

Predicting neoadjuvant therapy response in breast cancer from preoperative biopsy via spatial-semantic-differential learning and interpretable clinicopathological-guided fusion.

Predicting pathological complete response (pCR) to neoadjuvant therapy (NAT) in breast cancer remains challenging due to high tumor heterogeneity and ...

Prediction of post-stroke brain swelling using biomechanical modelling and deep neural networks.

Malignant stroke is a life-threatening condition, with mortality rates reaching up to 80% among patients managed conservatively. Brain swelling volume...

Constructing a corpus of hematologic pathology notes for the fine-tuning of BERT models for named entity recognition.

BACKGROUND: Microscopic, immunologic, and chemical testing play a major role in the diagnostic process of hematologic cancer patients. Pathologists re...

Clinical and immunological significance of FOXO1 as a biomarker of improved response to immune checkpoint plus tyrosine kinase inhibitor therapy in metastatic renal cell carcinoma.

BACKGROUND: Predicting response to immune checkpoint inhibitor plus tyrosine kinase inhibitor (IO+TKI) therapy in metastatic renal cell carcinoma (mRC...

Artificial Intelligence-Assisted reflectance confocal microscopy for Real-Time intraoperative margin assessment in oral squamous cell carcinoma.

BACKGROUND: Oral cavity squamous cell carcinoma (OSCC) is a global health burden, where negative margins are essential for reducing recurrence and imp...

Non-lethal molecular biomonitoring of pyrethroid exposure in freshwater fish using FTIR spectroscopy and machine learning.

Pyrethroid pesticides such as lambda-cyhalothrin (LC) continue to pose substantial risks to freshwater ecosystems, where sublethal exposures may impai...

Transcriptomic Plasticity Is a Hallmark of Metastatic Pancreatic Cancer.

UNLABELLED: Metastasis is the leading cause of cancer deaths. To develop strategies for intercepting metastatic progression, a better understanding of...

Multicenter Histology Image Integration and Multiscale Deep Learning Support Machine Learning-Enabled Pediatric Sarcoma Classification.

UNLABELLED: Pediatric sarcomas present diagnostic challenges due to their rarity and diverse subtypes, often requiring specialized pathology expertise...

Fuzzy-logic-driven predictions of multi-tissue ingrowth for rapid screening of mechanically instructive tissue-engineering scaffolds.

High retear rates in surgical intervention of interfacial/transitional tissues (bone-tendon, bone-ligament) drive a need to design tissue engineering ...

Malignant vs. Non-malignant Annotations on TCGA Breast Cancer Whole Slide Images for AI Analysis.

Identification of malignant and non-malignant regions in breast cancer whole slide images (WSIs) is essential for understanding tumor heterogeneity an...

Photon-counting Detector CT Spectral Reconstructions for Radiomics-based Liver Lesion Classification: A Multicenter Study.

OBJECTIVES: Accurate noninvasive classification of hepatic lesions remains a diagnostic challenge, particularly on conventional CT. Photon Counting De...

Cardiology at the Threshold of a New Biological Era: The Role of Multiomics and Metabolomics.

Modern cardiology is entering a phase where improving the prevention, diagnosis, and treatment of cardiovascular diseases (CVD) necessitates a deeper ...

Utilizing natural language processing (NLP) to identify breast cancer-associated lung metastases from pathology reports to delineate characteristics of this site of recurrence.

PURPOSE: Natural language processing (NLP, artificial intelligence) can enable automated identification of records in large datasets. The purpose of t...

Atomic-resolution imaging of gold species at organic liquid-solid interfaces.

The structure and dynamics of adsorbed atoms (adatoms) at solid-liquid interfaces determine the performance of advanced catalysts, electrochemical dev...

Multimodal AI model for early detection of hepatocellular carcinoma.

Detection of early hepatocellular carcinoma (eHCC) is important for timely treatment and improved prognosis. However, it is challenging to distinguish...

Automated Detection and Classification of Pleural Effusion on Computed Tomography Using Deep Learning.

The aim of this study is to develop and evaluate the performance of a two-stage deep learning-based artificial intelligence framework for the automati...