Pathology

Applications of visualization technology in the structural sciences.

The structural sciences are undergoing a transformation driven by advancements in visualization technologies that aid researchers in understanding and communicating experimental data from complex molecular systems. New applications of integrative structural biological and biophysical approaches add a wide variety of complementary information from a broad range of scientific disciplines. These appr...

Subregion-based radiomics analysis for predicting the histological grade of clear cell renal cell carcinoma.

PURPOSE: We explored the feasibility of constructing machine learning (ML) models based on subregion radiomics features (RFs) to predict the histological grade of clear cell renal cell carcinoma (ccRCC) and explore the molecular biological mechanisms associated with RFs.

Mechanistic exploration of hexokinase 2 and metabolism in diabetic cardiomyopathy.

The pathogenesis of diabetic cardiomyopathy (DCM) remains incompletely understood. The present study employed weighted gene co‑expression network anal...

Machine learning-driven prognostic model based on sphingolipid-related gene signature in pancreatic cancer: development and validation.

BACKGROUND: Pancreatic cancer, a highly malignant tumor with poor prognosis, lacks effective early diagnosis and treatment strategies. Sphingolipids h...

An Integrated AI-PBPK Platform for Predicting Drug In Vivo Fate and Tissue Distribution in Human and Inter-Species Extrapolation.

Optimal pharmacokinetic (PK) profile, including tissue distribution, is pivotal for a drug achieving success in clinical trials. Traditionally, PK est...

Does Machine Learning Prediction of Magnetic Resonance Imaging PI-RADS Correlate with Target Prostate Biopsy Results?

OBJECTIVES: This study aimed to predict and classify MRI PI-RADs scores using different machine learning algorithms and to detect the concordance of P...

Deep learning model for malignancy prediction of TI-RADS 4 thyroid nodules with high-risk characteristics using multimodal ultrasound: A multicentre study.

The automatic screening of thyroid nodules using computer-aided diagnosis holds great promise in reducing missed and misdiagnosed cases in clinical pr...

A Domain-Specific Pretrained Model for Detecting Malignant and Premalignant Ocular Surface Tumors: A Multicenter Model Development and Evaluation Study.

Malignant and premalignant ocular surface tumors (OSTs) can be sight-threatening or even life-threatening if not diagnosed and treated promptly. Artif...

The development of predictive biomarkers and immunologic markers for breast cancer: current status and future perspectives.

Breast cancer is the leading cause of cancer-related mortality among women worldwide. The development of predictive biomarkers and immunologic markers...

Uncovering codon usage patterns during murine embryogenesis and tissue-specific developmental diseases.

INTRODUCTION: Mouse models share significant genetic similarities with humans and have expanded our understanding of how embryonic tissue-specific gen...

MobNas ensembled model for breast cancer prediction.

Breast cancer poses a real and immense threat to humankind, thus a need to develop a way of diagnosing this devastating disease early, accurately, and...

Machine learning-based radiomics analysis in enhancing CT for predicting pathological subtypes and WHO staging of thymic epithelial tumors: a multicenter study.

This study is aimed to develop predictive models for classifying thymic epithelial tumor (TET) histological subtypes (A/AB/B1, B2/B3, C) and WHO stage...

Prognostic model identification of ribosome biogenesis-related genes in pancreatic cancer based on multiple machine learning analyses.

BACKGROUND: Pancreatic cancer is a highly aggressive cancer characterized by low survival rate. Enhanced ribosome biogenesis may be associated with tu...

An overview of recent advancements in 4D printing of alginate hydrogels for tissue regeneration.

4D printing of alginate hydrogels has emerged as a transformative strategy in tissue engineering, enabling the fabrication of stimuli-responsive scaff...

Image guided construction of a common coordinate framework for spatial transcriptome data.

Spatial transcriptomics is a powerful technology for high-resolution mapping of gene expression in tissue samples, enabling a molecular level understa...

Multimodal Explainable Artificial Intelligence for Prognostic Stratification of Glioblastoma Patients.

Glioblastoma is the most common and aggressive malignant adult tumor of the central nervous system, with a grim prognosis and heterogeneous morphologi...

Integrative machine learning and bioinformatics analysis unveil key genes for precise glioma classification and prognosis evaluation.

Gliomas exhibit significant heterogeneity and diverse molecular subtypes, and there are marked differences in treatment strategies and prognoses for g...

The Role of Hydrogen Sulfide in the Localization and Structural-Functional Organization of p53 Following Traumatic Brain Injury: Development of a YOLO Model for Detection and Quantification of Apoptotic Nuclei.

Traumatic brain injury (TBI) triggers a cascade of molecular and cellular disturbances, including apoptosis, inflammation, and destabilization of neur...

MSFusion: A multi-source hybrid feature fusion network for accurate grading of invasive breast cancer using H&E-stained histopathological images.

Invasive breast cancer (IBC) is a prevalent malignant tumor in women, and precise grading plays a pivotal role in ensuring effective treatment and enh...

Mitigating bias in prostate cancer diagnosis using synthetic data for improved AI driven Gleason grading.

Prostate cancer (PCa) is a leading cause of cancer-related mortality in men, with Gleason grading critical for prognosis and treatment decisions. Mach...