Pathology

Deep learning-based breast cancer detection with customized ensemble attention.

Breast cancer remains one of the leading malignancies globally, and accurate diagnostic decisions at...

Pleiotropy and disease interactors: the dual nature of genes linking ageing and ageing-related diseases.

Ageing-related diseases (ARDs) display diverse phenotypes yet share an age-dependent rise in inciden...

The Role of Molecular Testing in Head and Neck Squamous Cell Carcinoma of Unknown Primary.

Squamous cell carcinomas of unknown primary (SCCUP), accounting for approximately 5% of head and nec...

Quantifying the Heterogeneity of TRUS-Visible Lesions for Predicting Prostate Cancer: A Multicenter Preliminary Study.

RATIONALE AND OBJECTIVES: This study aimed to quantitatively characterize the heterogeneity of Trans...

Quantitative whole-body measurement of inflammothrombotic immunologic response disease using Fleming method for tissue and vascular differentiation and metabolism.

BACKGROUND: Precision theranostics in nuclear medicine requires reproducible, calibrated quantificat...

Volumetric phase-specific three-dimensional radiomics and machine learning for differentiation of non-mass enhancement in breast magnetic resonance imaging.

PURPOSE: Non-mass enhancement (NME) in breast magnetic resonance imaging (MRI) is a diagnostically c...

Glioblastoma region-specific metabolic signatures reflect patient survival duration.

PURPOSE: Spatial metabolic differences found in glioblastoma (GBM) tumor core (contrast enhancing) a...

DiffBulk: Enhancing Spatial Transcriptomic Prediction with Diffusion-Based Training.

Spatial Transcriptomics (ST) technology detects gene expression from tissue biopsies, playing an eme...

[Current status of artificial intelligence applications in cervical cancer screening: a systematic review].

Objective: To systematically summarize and evaluate the current application status and research prog...

Stacked CT radiomics, deep learning and clinical feature models for differentiating benign and malignant solitary pulmonary nodules.

Counterfactual Reasoning for Mammogram Classification via Semantic Texture Masking.

Artificial intelligence-based computer-aided diagnosis (CADx) systems have seen growing adoption in ...

Single-molecule localization and diffusivity microscopy reveals dynamic biomolecular organization in living cells.

Single-molecule tracking in living cells measures protein diffusivity but requires sparse imaging, l...

A multiobjective AI model for LNP engineering enhances tissue-selective mRNA delivery.

Lipid nanoparticle (LNP) delivery of RNA therapeutics is constrained by poor tissue selectivity and ...

A novel system design for monocular laser assisted capsule endoscopy for 3D small bowel modeling.

The long, tortuous, and tissue-homogeneous structure of the small bowel makes image-based three-dime...

Harnessing Artificial Intelligence for the Management of Patients With GI Cancers.

Artificial intelligence (AI) has the potential of reshaping GI oncology by enabling more nuanced int...

Advances in Digital Cytopathology and Artificial Intelligence Applications.

Cytopathology is the first field of pathology in which artificial intelligence (AI) models were succ...

Artificial Intelligence-Enabled Analysis of Radiology Reports: Epidemiology and Outcomes of Incidental Thyroid Findings.

CONTEXT: Incidental thyroid findings (ITFs) are increasingly detected on imaging performed for non-t...

Implementation of pathogen genomics in clinical microbiology laboratories.

SUMMARYPathogen genomics, including whole-genome sequencing (WGS) and clinical metagenomics, is a tr...

Gram staining decipherment using an artificial intelligence-powered smartphone-based application.

Gram staining provides rapid microbiological information that may assist in empirical antimicrobial ...

Unsupervised Semantic Segmentation Models for Region of Interest Identification.

Spatial omics technologies, such as mass spectrometry imaging (MSI), can capture biomolecular distri...

MetaXVP: an interpretable machine learning framework for deep insight into variant pathogenicity and VUS classification.

The interpretation and classification of nonsynonymous single nucleotide variants (nsSNVs) remains a...