Pathology

An Interpretable Deep-Learning Approach for Efficient CEST Parameter Quantification: Importance-Ranked Saturation Transfer MRI Protocol.

PURPOSE: An optimal design of saturation-transfer MR fingerprinting (ST-MRF) sequences is essential to accelerate imaging and improve tissue quantification accuracy. This study aims to develop an interpretable deep-learning framework, importance-ranking network (IRnet), which can rank and identify the most informative dynamic scans, enabling optimized acquisition with a minimal number of scans whi...

Near-infrared imaging-based high-content analysis for label-free assessment of internal cellular heterogeneity in spheroid.

Non-invasive analysis of spheroid quality was essential because spheroids better recapitulated in vivo-like cell-cell and cell-extracellular matrix (ECM) interactions than two-dimensional cultures. However, routine non-invasive methods to assess internal structural heterogeneity remained limited. Here, we developed a near-infrared imaging-based high-content analysis (NIR-HCA) approach to non-destr...

STAID: A Self-Refining Deep Learning Framework for Spatial Cell-Type Deconvolution with Biologically Informed Modeling.

Spatial transcriptomics provides high-throughput measurement of gene expression while retaining spatial context; however, inferring accurate cell-type...

Validation, implementation, and impact of an AI model in routine practice for pathologic diagnosis of prostate cancer in an academic medical center.

BACKGROUND: Pathological evaluation of prostate needle biopsies is labor-intensive and often requires ancillary immunohistochemistry (IHC), increasing...

Artificial intelligence model predicts malignant transformation of oral leukoplakia and optimizes interventions.

PURPOSE: Oral leukoplakia (OL), the most common oral potentially malignant disorder (OPMD), poses a significant risk for transformation to oral squamo...

Integrating machine learning and single-cell sequencing to reveal the role of kinase-related genes in subtype classification and prognostic significance of lung squamous cell carcinoma.

BACKGROUND: Lung squamous cell carcinoma (LUSC) exhibits poor prognosis and a highly complex tumor immune microenvironment (TIME), creating an urgent ...

Advanced computer-aided diagnosis for age-related macular degeneration: integrating segmentation and feature extraction for precise diagnosis.

Age-related Macular Degeneration (AMD) is a leading cause of vision loss globally; necessitating early detection and precise diagnosis for effective i...

Explainable artificial intelligence with pyramid vision transformer model for multi-class malignant cell classification on cytology slides.

Digital pathology involves the digitisation of histology slides, which is vital in modern healthcare, especially for cancer detection and diagnosis. S...

Photon absorption remote sensing (PARS): comprehensive absorption imaging enabling label-free biomolecule characterization and mapping.

Label-free optical absorption microscopy techniques continue to evolve as promising tools for label-free histopathological imaging of cells and tissue...

Integration of transcriptome and DNA methylation reveals the mechanism of cilia-related genes in recurrent miscarriage.

Recurrent miscarriage (RM), a complex pregnancy disorder with largely undefined molecular mechanisms, has been associated with epigenetic abnormalitie...

AI as a differentiated cognitive partner in medical education: a comparative study of popular science versus research-based curriculum extensions in histology and embryology.

OBJECTIVE: This study compared the efficacy of Popular Science (PS) and Research-Based (RS) curriculum extensions in a Histology and Embryology course...

Deep learning based on CD3 histological slides for prediction of colon cancer outcome: analysis of three international stage III colon cancer cohorts.

Prognostic stratification in stage III colon cancer remains poor, despite treatment advances. Tumor-infiltrating lymphocytes, particularly CD3+ T cell...

Machine learning and multi-dimensional transcriptomics reveal the key molecular network of benzo(a)pyrene/NNK in promoting laryngeal cancer and develop prognostic models.

Benzo(a)pyrene (BaP) and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK), as typical environmental carcinogens, are widely present in tobacco smo...

AI-predicted spatial transcriptomics unlocks breast cancer biomarkers from pathology.

Spatial transcriptomics (ST) assays are transforming our understanding of tumor heterogeneity, but their high cost limits their application in large-s...

Three Data-Driven Lip Soft-Tissue Phenotypes and Their Dento-Skeletal Associations in Orthodontic Patients: An Exploratory Unsupervised Learning Study.

BACKGROUND: Conventional facial diagnosis emphasizes skeletal and dental measures while lip features are assessed piecemeal. We aimed to identify data...

Lineage Classification of Pituitary Neuroendocrine Tumors From Whole-Slide Images Using Attention-Guided Graph Representation Learning.

Pituitary neuroendocrine tumors (PitNETs) are common sellar neoplasms and represent a major component of routine pituitary pathology. In the 2022 Worl...

Integrative analysis of tumor-educated platelets for stage-specific diagnosis, prognosis, and therapy in ovarian cancer.

BACKGROUND: Ovarian cancer (OC) remains one of the most lethal gynecological cancers worldwide. Despite advances in diagnosis, OC is mostly detected a...

Machine learning-based integration of transcriptome and digital pathology for predicting chemoresistance in muscle-invasive bladder cancer.

Muscle-invasive bladder cancer (MIBC) presents with variable clinical and pathological features, leading to inconsistent responses to standard treatme...

Consistency analysis of AI cell recognition results between non anticoagulant and anticoagulant marrow smear after Wright's staining.

The integration of artificial intelligence with bone marrow cytology represents a significant trend in the application of AI image recognition technol...

Multi-omics analysis of the mechanism by ATP13A2 regulates the tumor microenvironment and prognosis in hepatocellular carcinoma.

BACKGROUND AND AIMS: Hepatocellular carcinoma (HCC) is a prevalent global cancer. Most patients with HCC are diagnosed at an advanced stage. Therefore...