Pathology

Geometric-aware deep learning for deciphering tissue structure from spatially resolved transcriptomics.

Recent advances in spatially resolved transcriptomics have enabled large-scale measurement of gene expression while preserving spatial context, facilitating the investigation of spatial heterogeneity within tissues. In this study, we propose SpatialGEO, a geometric-aware deep learning framework that integrates gene expression profiles with spatial coordinates to generate biologically meaningful lo...

A novel attention mechanism for noise-adaptive and robust segmentation of microtubules in microscopy images.

BACKGROUND: Segmenting cytoskeletal filaments in microscopy images is essential for studying their roles in cellular processes such as cell division and intracellular transport. However, this task is highly challenging due to the fine, densely packed, and intertwined nature of these structures. Imaging limitations-noise, low contrast, and uneven fluorescence-further complicate analysis. While deep...

Deep learning-based classification of gh-secreting pituitary neuroendocrine tumors granulation patterns using H&E-stained histopathology.

Accurate classification of granulation patterns in growth hormone-secreting pituitary neuroendocrine tumors (GH-PitNETs) is clinically essential but t...

Deep learning-based malignancy probability estimation of pulmonary nodules in PET/CT imaging.

OBJECTIVE: The current BTS guidelines recommend evaluation of suspicious pulmonary nodules using [18F]FDG-PET/CT imaging, followed by Herder model ris...

Integrating epigenetic and metabolic indicators for non-invasive endometrial cancer triage: a machine learning approach.

OBJECTIVE: Abnormal uterine bleeding (AUB) is a primary symptom indicative of endometrial cancer (EC), yet its diagnosis still primarily relies on inv...

Comparison of radiomics handcrafted features and deep features in 18F-FDG PET/CT for differentiating benign and malignant persistent pulmonary ground-glass nodules.

BACKGROUND: The differentiation between benign and malignant persistent pulmonary ground-glass nodules (GGNs) remains challenging, and the relative va...

Glycosylation Signatures of Thyroglobulin in Papillary Thyroid Carcinoma.

Thyroglobulin (Tg) is a clinically established biomarker for thyroid cancer; however, its diagnostic specificity remains limited due to confounding be...

Bionic Magnetic Nanorobots Combined with AI-Assisted Microscopic Imaging for Argonaute-Powered Multiplexed Foodborne Pathogens Detection.

Multiplexed and ultrasensitive identification of foodborne pathogens is crucial for food safety. However, conventional methods are limited by complex ...

Combining pathology artificial intelligence and genomic biomarkers to refine long-term postprostatectomy outcome prediction.

BACKGROUND: A multimodal AI (MMAI) model has been validated in prostate biopsy specimens to guide treatment intensification in men receiving radiation...

Atomic force microscopy in lung cancer: from mechanobiology to clinical translation.

Atomic force microscopy (AFM) enables the nanoscale investigation of cellular mechanics, morphology, and molecular interactions under conditions that ...

Machine learning integration of tissue-specific metagenomic signatures for colorectal cancer diagnosis.

Colorectal cancer (CRC) represents a significant global health burden. Leveraging machine learning (ML) with metagenomic and tissue-specific data pres...

Artificial Intelligence for Cervical HPV Infection and Lesion Screening: A Cross-Sectional Analysis of Its Application Potential and Patient Satisfaction.

OBJECTIVE: This cross-sectional study aimed to explore the application potential of artificial intelligence (AI) in screening and diagnosing cervical ...

Antibody-drug conjugates in selected solid tumours: a position statement update based on findings from the third workshop held by the ETOP IBCSG Partners Foundation.

The European Thoracic Oncology Platform (ETOP) International Breast Cancer Study Group (IBCSG) Partners Foundation initiated a series of workshops for...

Image-guided multiscale modeling of trabecular bone: lacuna-resolved stress amplification and interaction effects.

Osteocyte lacunae are ubiquitous microstructural cavities in bone that perturb local stress and strain fields, shaping the mechanical microenvironment...

Comparative Diagnostic Performance of Large Language Models and Clinicians for Splenic Diseases in Dogs and Cats.

Splenic diseases in dogs and cats present significant diagnostic challenges, particularly in differentiating benign from malignant lesions using conve...

Pulmonary nodule prediction in the multi-omics era: integrating radiomics, AI, liquid biopsy, and airway classifiers.

Low-dose CT (LDCT) lung cancer screening significantly reduces mortality but has dramatically increased the detection of pulmonary nodules. Most of th...

Promise and pragmatism of AI in global-scale digital pathology: pan-cancer approaches for clinical practice.

Artificial intelligence (AI) tools for digital pathology have crossed the threshold from pilot project to clinical deployment, with regulatory approva...

A Multimodal Multitask Deep Learning Model Based on Ultrasound RF Signals for Joint Assessment of Breast Masses and Axillary Lymph Nodes Status.

PURPOSE: Developing a deep learning model to simultaneously evaluate lymph node status and distinguish between benign and malignant breast masses has ...

Development of an expert-annotated chest X-ray dataset to support AI validation in tuberculosis diagnosis.

OBJECTIVES: To assess inter-rater agreement and diagnostic performance of six United States National Institute for Occupational Safety and Health-cert...

Factors contributing to the missed diagnosis of incidental gallbladder cancer (IGBC): an integrated analysis of clinical features and ultrasound radiomics.

BACKGROUND: Incidental gallbladder cancer (IGBC) is often diagnosed only during or after cholecystectomy, and preoperative identification remains chal...