Latest AI and machine learning research in pathology for healthcare professionals.
RATIONALE AND OBJECTIVES: This study aimed to quantitatively characterize the heterogeneity of Transrectal ultrasound (TRUS)-visible lesions using subregional imaging analysis, and to develop and validate an intratumoral heterogeneity (ITH) model for differentiating prostate cancer (PCa) from benign lesions. MATERIALS AND METHODS: This retrospective study included patients from three medical cente...
BACKGROUND: Precision theranostics in nuclear medicine requires reproducible, calibrated quantification of tissue perfusion, and metabolism. This study evaluates whether the Fleming method for tissue and vascular differentiation and metabolism (FMTVDM) can quantify inflammothrombotic immunologic response disease (ITIRD) as a unified biologic continuum across cardiovascular, oncologic, and infectio...
PURPOSE: Non-mass enhancement (NME) in breast magnetic resonance imaging (MRI) is a diagnostically challenging entity due to overlapping benign and ma...
PURPOSE: Spatial metabolic differences found in glioblastoma (GBM) tumor core (contrast enhancing) and peritumoral (T2/FLAIR hyperintense) edge tissue...
Spatial Transcriptomics (ST) technology detects gene expression from tissue biopsies, playing an emerging role in cancer diagnosis and precision medic...
Objective: To systematically summarize and evaluate the current application status and research progress of artificial intelligence (AI) in cervical c...
Artificial intelligence-based computer-aided diagnosis (CADx) systems have seen growing adoption in mammography, yet the limited interpretability of t...
Single-molecule tracking in living cells measures protein diffusivity but requires sparse imaging, limiting high-density mapping. Here we introduce si...
Lipid nanoparticle (LNP) delivery of RNA therapeutics is constrained by poor tissue selectivity and off-target toxicity. Most high-throughput screenin...
The long, tortuous, and tissue-homogeneous structure of the small bowel makes image-based three-dimensional (3D) modeling studies technically complex....
Artificial intelligence (AI) has the potential of reshaping GI oncology by enabling more nuanced interpretation of complex clinical, imaging, and mole...
MOTIVATION: Understanding pan-cancer level mutational landscape offers critical insights into the molecular mechanisms underlying tumorigenesis. While...
Cytopathology is the first field of pathology in which artificial intelligence (AI) models were successfully developed and commercialized for routine ...
CONTEXT: Incidental thyroid findings (ITFs) are increasingly detected on imaging performed for non-thyroid indications. Their prevalence, features, an...
SUMMARYPathogen genomics, including whole-genome sequencing (WGS) and clinical metagenomics, is a transformative technology increasingly being impleme...
Gram staining provides rapid microbiological information that may assist in empirical antimicrobial selection; however, the results are often interpre...
Spatial omics technologies, such as mass spectrometry imaging (MSI), can capture biomolecular distributions and their spatial locations directly from ...
The interpretation and classification of nonsynonymous single nucleotide variants (nsSNVs) remains a significant challenge in clinical genomics partic...
Recent advances in spatial transcriptomics (ST) have generated an expanding collection of heterogeneous datasets, offering unprecedented opportunities...