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Journal of Pathology Informatics
Scopus
ISSN 2153-3539 · Elsevier · 1.123 artikel di indeks
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Artikel Jurnal
Applications and challenges of utilizing digital pathology and AI-enabled workflows in clinical trials
This is a comprehensive review on current utilization and challenges of digital pathology adoption in clinical trials and aims to provide a broad view on its impact on pathology review processes in clinical trials. It provides an overview of current pathology review practices in clinical trials and…
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Artikel Jurnal
Comparison of digital displays for efficient diagnosis and accuracy
Digital pathology is transforming diagnostic workflows by enabling the interpretation of whole-slide images on digital displays, offering advantages in remote diagnostics, efficiency, and integration with computational tools. However, diagnostic reliability depends not only on scanner and software…
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Artikel Jurnal
Transforming multi-omics data into images for disease classification: A review of techniques and tools
The integration of multi-omics data has become crucial in understanding the complexity of biological systems and disease mechanisms. However, the high dimensionality and heterogeneity of such data present significant analytical challenges. This review investigates the emerging approach of…
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Artikel Jurnal
A machine learning model of lamina propria fibrosis in eosinophilic esophagitis for prediction of fibrostenotic disease
Background: Eosinophilic esophagitis (EoE) is a chronic immune-mediated disease that can progress to fibrostenotic complications. Lamina propria fibrosis (LPF) plays a critical role in this progression but is difficult to assess reliably in routine biopsies. We aimed to develop and validate an…
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Artikel Jurnal
ADPv2: A hierarchical histological tissue type-annotated dataset for potential biomarker discovery of colorectal disease
Computational pathology (CPath) leverages histopathology images to enhance diagnostic precision and reproducibility in clinical pathology. However, publicly available datasets for CPath that are annotated with extensive histological tissue type (HTT) taxonomies at a granular level remain scarce due…
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Artikel Jurnal
PANDA-PLUS: Improved dataset of prostate whole slide images from PANDA Challenge with pixel-level expert annotations
Artificial intelligence (AI)-based prostate cancer detection through whole slide images (WSIs) offers promising potential to address the global pathologist shortage while improving clinical consistency. Digital slides and improving image analysis methods encourage the creation of tools to aid in…
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Artikel Jurnal
Biological feature-based machine learning in histopathological images: a systematic review
Digital pathology has recently led to significant advancements in the field of microscopic image analysis, particularly regarding the increasing use of Deep Learning methods. These models represent the state-of-the-art in histopathological slide analysis, but Deep Learning features remain difficult…
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Artikel Jurnal
An integrated system from microscopy to AI for real-time object detection in endometrial cytology
Endometrial cytology, which is minimally invasive and available as an outpatient procedure, is widely used in Japan for early detection of endometrial cancer, but its diagnostic process is time-consuming and requires expert diagnosticians. We developed a real-time artificial intelligence…
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Artikel Jurnal
Developing a smart and scalable tool for histopathological education—PATe 2.0
Digital microscopy plays a crucial role in pathology education, providing scalable and standardized access to learning resources. In response, we present PATe 2.0, a scalable redeveloped web-application of the former PATe system from 2015. PATe 2.0 was developed using an agile, iterative process…
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Artikel Jurnal
Digital pathology imaging artificial intelligence in cancer research and clinical trials: An NCI workshop report
Digital pathology imaging (DPI) is a rapidly advancing field with increasing relevance to cancer diagnosis, research, and clinical trials through large-scale image analysis and artificial intelligence (AI) integration. Despite these advances, regulatory adoption in digital pathology (DP) has…
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Artikel Jurnal
Technical considerations during validation of the Genius® Digital Diagnostic System
Background: The aim of this study was to document technical errors encountered during validation of the Genius Digital Diagnostics System (GDDS). Materials and methods: A total of 909 cases of archived ThinPrep Pap slides with follow-up biopsies were retrieved. Slides were cleaned, relabeled, and…
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Artikel Jurnal
Leveraging sequence-to-sequence models for semantic annotation of Dutch pathology reports
Palga Foundation is responsible for indexing Dutch pathology data across the Netherlands, which relies on annotations of pathology reports. These annotations, derived from the conclusion text, consist of codes from the Palga thesaurus, serving patient care and scientific research. However, manual…
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Artikel Jurnal
MuCoSA: Multi-contextual similarity assessment for histopathology image search
Histological diagnosis in pathology often begins with visual identification of morphological patterns that resemble known disease entities. Whereas digital pathology and augmented intelligence have enabled reverse image search in histopathology, most existing frameworks rely on single-magnification…
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Artikel Jurnal
Iris RESTful Server and IrisTileSource: An Iris implementation for existing OpenSeaDragon viewers
The Iris File Extension (IFE) is a low overhead performance-oriented whole-slide image (WSI) file format designed to improve the image rendering experience for pathologists and simplify image management for system administrators. However, static hypertext transfer protocol (HTTP) file servers…
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Artikel Jurnal
HistoEncoder: A digital pathology foundation model for prostate cancer
Foundation models are trained on massive amounts of data to capture complex patterns in images. Subsequently, a wide range of downstream tasks can be adopted with minimal computational resources. We have developed HistoEncoder, a foundation model for prostate cancer digital pathology by…
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Artikel Jurnal
CellPrior-net: Prior-guided nuclei detection and classification for H&E whole-slide images
Accurate nuclei detection and classification in hematoxylin and eosin (H&E) whole-slide images (WSIs) is a key task in computational pathology, particularly for quantitative analysis of the tumor microenvironment. However, this task remains highly challenging due to variations in nuclei morphology…
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Artikel Jurnal
How does AI perform compared to human expert panels in medical Delphi studies? A pilot study through the lens of pathology
Background: Since their inception, Delphi studies have been a key part of medical literature. They consist of an expert panel tasked with coming to consensus on answers to various questions where obtaining objective results is difficult or impossible, with ranked responses based on a Likert scale…
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