Pathology

Integrative bioinformatics analysis unveils neuro-cancer crosstalk-related genes and establishes prognostic risk model in Glioblastoma.

Neuro-cancer crosstalk plays an important role in the development and progression of Glioblastoma (GBM), but its specific mechanisms remain incompletely elucidated. This study aims to systematically identify key genes related to neuro-cancer crosstalk in GBM and construct a prognostic risk model through integrating single-cell RNA sequencing (scRNA-seq), bulk RNA-seq, and machine learning algorith...

Cross-cancer homologous recombination deficiency prediction from whole slide images using transfer learning.

Accurate prediction of Homologous Recombination Deficiency (HRD) is vital for personalized cancer therapy, yet genomic assays are often costly and complex. Predicting HRD from Hematoxylin and Eosin (H&E) stained whole-slide images (WSIs) via deep learning offers an alternative, but model generalization across diverse cancer types remains challenging. We developed a three-stage transfer learning fr...

Performance and generalization analysis of machine learning, deep learning, and transformer models for histopathology image classification.

Histopathology image classification plays a critical role in computer-aided diagnosis by supporting pathologists in disease detection and grading. Wit...

The evolution of prostate cancer grading: from Gleason score to risk taxonomy and the artificial intelligence revolution.

Histopathological grading remains the cornerstone of risk stratification in prostate cancer, yet conventional Gleason-based assessment is limited by i...

SPECTRAL: An Intelligent and Ultra-Sensitive Photonic Hydrogel Platform for Biomarker-Based Cancer Prediction.

Point-of-care (POC) biosensing holds great promise for noninvasive cancer diagnostics, as circulating tumor DNA (ctDNA) serves as a minimally invasive...

Gliomas as network diseases: Neuron-tumor interactions, connectome disruption, and clinical implications.

BACKGROUND: Gliomas are increasingly understood as disorders of distributed brain networks rather than focal lesions confined within radiographic marg...

Tubulointerstitial Diseases: An Updated Framework for Diverse and Emerging Entities.

Tubulointerstitial diseases represent a heterogeneous group of kidney diseases with diverse causes and overlapping histopathologic and immunophenotypi...

Decoding Parkinson's progression: A multi-modal SuStaIn ensemble approach validated on real-world PPMI data.

BACKGROUND: Parkinson's disease (PD) exhibits substantial heterogeneity in clinical presentation and longitudinal progression, complicating prognosis,...

Performance of multimodal large language models for the detection and characterization of bone lesions on radiographs.

PURPOSE: Multimodal large language models (LLMs) offer emerging capabilities in medical image interpretation; however, their efficacy in orthopedic on...

Assessing the Reliability of MRI and CT Scans for Liver Volume Estimation in Patients Undergoing Liver Transplantation.

OBJECTIVE: Magnetic resonance imaging (MRI) and computed tomography (CT) are commonly used to measure organ volumes, but accuracy has not been methodi...

Instance-Aware Pseudo-Labeling and Class-Focused Contrastive Learning for Weakly Supervised Domain Adaptive Segmentation of Electron Microscopy.

Annotation-efficient segmentation of the numerous mitochondria instances from various electron microscopy (EM) images is highly valuable for biologica...

Machine learning-based integration of respiratory oscillometry and spirometry for predicting clinical outcomes in spinal muscular atrophy.

UNLABELLED: Assessing respiratory function in spinal muscular atrophy (SMA) is challenging due to the effort-dependent nature of traditional spirometr...

Characterization of telomere-related gene subtypes in lung adenocarcinoma and their implications for prognosis and treatment.

BACKGROUND: Telomeres, located at chromosome ends, regulate cell division and maintain genomic stability. Telomere-related genes (TRGs) play essential...

Advances in Radiotherapy for Soft Tissue Sarcomas in 2025: A Review.

PURPOSE OF REVIEW: This review aims to synthesize and critically appraise the most impactful advances in radiotherapy (RT) for soft tissue sarcomas (S...

Integrated imaging-informed and machine learning-based prognostic models for risk stratification in connective tissue disease-associated interstitial lung disease: a multicenter study.

OBJECTIVES: Connective tissue disease-associated interstitial lung disease (CTD-ILD) exhibits heterogeneous clinical outcomes, and traditional ILD-GAP...

Human-to-Rat Validation of PMI Biomarkers: A Bidirectional Cross-Species Metabolomics Study Reveals Asymmetric Translation.

Accurately estimating the post-mortem interval (PMI, also known as time since death) remains a major challenge in forensic science due to substantial ...

The potential role of artificial intelligence in the diagnosis of Acanthamoeba keratitis-a scoping review.

BACKGROUND: Acanthamoeba keratitis (AK) is a severe, sight-threatening infectious disease with a rising global incidence, linked to the increasing use...

Machine learning-driven discovery of therapeutic nucleoside hydrogels for periodontitis.

Supramolecular hydrogels hold significant potential in drug delivery and tissue engineering, with standing out for their unique properties. Despite th...

BC-SwinNet: Swin transformer and CNN with multi-objective optimization for multi-class breast cancer detection using Histopathological images.

Breast cancer remains a major global health concern and is the leading cause of cancer-related deaths among women worldwide. It is estimated that by 2...

Abstraction-dependent diagnostic performance of a multimodal foundation model in oral epithelial dysplasia.

The reliability of general-purpose multimodal large language models (LLMs) in oral histopathologic image interpretation remains incompletely character...