Pathology

Machine Learning Prediction of Liver Fibrosis in Patients with Metabolic Dysfunction Associated Steatotic Liver Disease (MASLD).

BACKGROUND: Accurate staging of liver fibrosis is crucial for risk stratification in patients with metabolic dysfunction-associated steatotic liver disease (MASLD). We aimed to develop and validate AI-based models capable of distinguishing fibrosis stages. METHODS: We developed and validated machine learning models to predict fibrosis stages in more than 3,600 biopsy-confirmed MASLD patients using...

AI-driven tumor heterogeneity quantification and survival prediction in pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies worldwide, and accurate prognostic prediction remains highly challenging due to its marked biological heterogeneity and complex tumor microenvironment. To address this challenge, a histopathomics-based survival prediction system (HPSurv) was developed using histopathological whole-slide images (WSIs) for individualized ...

ABUS-ResMask-Net: ABUS Lesion Classification Network Design with ResMask Module and BI-RADS Content-Awareness Auxiliary Tasks.

This study aims to develop a 2.5D deep learning model with shape and margin as auxiliary tasks to improve the diagnostic performance of benign-maligna...

Screening of shared molecular markers between cervical cancer and major depressive disorder and the mechanism of CRAT/CLIC4 regulating EMT in cervical cancer cells.

BACKGROUND: Cervical cancer (CC) ranks among the most prevalent malignant neoplasms affecting women worldwide. Tumor recurrence, distant metastases, a...

Beyond visual inspection: can a multimodal machine learning model improve the preoperative differentiation of endometrial polyps from non-polypoid endometrial lesions?

OBJECTIVE: To develop a multimodal machine learning model that integrates clinical data and ultrasound features to improve the non‑invasive preoperati...

An evidence informed framework for artificial intelligence in rare breast cancers using small cohort validation synthetic data practices and clinical governance.

Rare breast cancers represent a clinically important but underrepresented group of malignancies. In this Perspective, rare breast cancers are consider...

Translational gaps and clinical readiness of artificial intelligence and multimodal imaging in breast cancer diagnostics.

BACKGROUND: A persistent translational gap separates the high research-benchmark performance of artificial intelligence (AI) and advanced imaging in b...

UK recommendations for Ki-67 immunohistochemical staining and interpretation in breast cancer.

Ki-67 is a well-established marker of tumour proliferation and an important prognostic and predictive biomarker in breast cancer, particularly in horm...

Investigating the mechanisms of malignant progression in colorectal cancer using weighted gene co-expression network analysis and machine learning.

Colorectal cancer (CRC) remains a leading cause of cancer-related mortality worldwide. Understanding the complex molecular networks that underlie this...

Association of Histological Features of Cortical and Medullary Peritubular Capillaries With Progressive CKD.

RATIONALE & OBJECTIVE: Peritubular capillary (PTC) rarefaction occurs in chronic kidney disease (CKD), but the independent association of PTC histolog...

FKBP10 may affect the malignant phenotype of oral squamous cell carcinoma cells through the ECM/WNT signaling pathway.

Oral squamous cell carcinoma (OSCC) is a common malignant tumor in the oral and maxillofacial region with a poor prognosis, and its pathophysiology ha...

Multimodal molecular mapping of the vasculature in human cortex reveals lipid markers of cerebral amyloid angiopathy.

Cerebral amyloid angiopathy (CAA) commonly co-occurs with Alzheimer's disease (AD), yet the molecular changes that accompany vascular [Formula: see te...

A serum-clinical composite model for prostate cancer diagnosis: multicenter validation and CRISPR/Cas13a-based detection.

BACKGROUND: Avoidable prostate biopsies remain a persistent weakness of prostate specific antigen (PSA)- and imaging-led prostate cancer (PCa) diagnos...

Mechanistic study on comorbidities of kidney stones and sepsis using transcriptome sequencing combined with single-cell spatial transcriptome sequencing.

Kidney stones and sepsis have a complex pathological association. Urinary obstruction and infection caused by kidney stones can easily induce sepsis, ...

Supervised artificial intelligence classification of clinker processing conditions by optical microscopy.

Optical microscopy is known to be a powerful technique for the characterization of industrial clinkers, allowing for obtaining valuable information on...

Mapping ovarian cellular and molecular landscape across the lifespan of women: a scoping review.

BACKGROUND: With growing interest in ART, fertility preservation, and postmenopausal health of women, reproductive medicine is increasingly focused on...

Protective Effects of p-Coumaric Acid Against Lead-Induced Hepatic Oxidative Stress, Inflammation, and Apoptosis: Integrated Molecular and Machine Learning-Based Analysis.

Lead (Pb) exposure is a major environmental health concern that induces hepatic injury through oxidative stress, inflammation, and apoptosis. This stu...

Current Perspectives on Thyroid Nodule Evaluation: Integrating Cytomorphology, Ultrasound Risk Stratification, and Molecular Testing.

Fine-needle aspiration biopsy (FNAB) remains the cornerstone of preoperative evaluation of thyroid nodules and represents one of the most enduring and...

Artificial Intelligence in Digital Pathology for Prostate Cancer Detection: FDA Clearance and Real-World Implementation.

Artificial intelligence (AI) has emerged as a promising adjunct in surgical pathology, particularly in the diagnosis of prostate cancer, where variabi...

A federated attention-based stacked LSTM framework for interpretable malaria diagnosis under simulated non-IID federated conditions.

Malaria remains a major global health burden, particularly in low-resource regions where microscopic diagnosis relies heavily on expert interpretation...