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View article: The STARD-AI reporting guideline for diagnostic accuracy studies using artificial intelligence
The STARD-AI reporting guideline for diagnostic accuracy studies using artificial intelligence Open
View article: Machine learning-based multimodal prognostic models integrating pathology images and high-throughput omic data for overall survival prediction in cancer: a systematic review
Machine learning-based multimodal prognostic models integrating pathology images and high-throughput omic data for overall survival prediction in cancer: a systematic review Open
Multimodal machine learning integrating histopathology and molecular data shows promise for cancer prognostication. We systematically reviewed studies combining whole slide images (WSIs) and high-throughput omics to predict overall surviva…
View article: Use of quality checks and processes across digital histopathology: an initial survey from the Bigpicture consortium
Use of quality checks and processes across digital histopathology: an initial survey from the Bigpicture consortium Open
Aims In the end-to-end digital pathology workflow, variability can be introduced at each step, resulting in differences in the final image dataset. The effectiveness of quality control processes at each step of the workflow will impact the…
View article: Development of a national pathology training system using digital pathology and SNOMED-CT
Development of a national pathology training system using digital pathology and SNOMED-CT Open
View article: Formative Usability Testing of Artificial Intelligence in Pathology: The Challenge of Assessing Acceptability
Formative Usability Testing of Artificial Intelligence in Pathology: The Challenge of Assessing Acceptability Open
Digital Pathology has provided a platform to use Artificial Intelligence (AI) to assist pathologists with diagnosis and reporting. An AI tool is being developed that analyzes digital Hematoxylin and Eosin (stained tissue) images associated…
View article: Supplementary File from MANIFEST: Multiomic Platform for Cancer Immunotherapy
Supplementary File from MANIFEST: Multiomic Platform for Cancer Immunotherapy Open
MANIFEST Consortium List of Authors
View article: Data from MANIFEST: Multiomic Platform for Cancer Immunotherapy
Data from MANIFEST: Multiomic Platform for Cancer Immunotherapy Open
Summary:Immunotherapy has revolutionized survival outcomes for many patients diagnosed with cancer. However, biomarkers that can reliably distinguish treatment responders from nonresponders, predict potential life-threatening and life-chan…
View article: Supplementary Table 1 from MANIFEST: Multiomic Platform for Cancer Immunotherapy
Supplementary Table 1 from MANIFEST: Multiomic Platform for Cancer Immunotherapy Open
Notable large-scale immuno-oncology consortia formed in the recent era.
View article: Liver-Quant: Feature-based image analysis toolkit for automatic quantification of metabolic dysfunction-associated steatotic liver disease
Liver-Quant: Feature-based image analysis toolkit for automatic quantification of metabolic dysfunction-associated steatotic liver disease Open
Liver-Quant offers an open-source solution for rapid and precise MASLD quantification in WSIs applicable to multiple histological stains.
View article: An international study of stain variability in histopathology using qualitative and quantitative analysis
An international study of stain variability in histopathology using qualitative and quantitative analysis Open
Hematoxylin and eosin (H&E) staining accounts for over 80% of slides stained worldwide. Although routinely used, there are high levels of variation between labs due to different staining methods. Staining is a pivotal part of slide prepara…
View article: Tackling algorithmic bias and promoting transparency in health datasets: the STANDING Together consensus recommendations
Tackling algorithmic bias and promoting transparency in health datasets: the STANDING Together consensus recommendations Open
View article: The Development and Evaluation of a Convolutional Neural Network for Cutaneous Melanoma Detection in Whole Slide Images
The Development and Evaluation of a Convolutional Neural Network for Cutaneous Melanoma Detection in Whole Slide Images Open
Context.— The current melanoma staging system does not account for 26% of the variance seen in melanoma-specific survival, therefore our ability to predict patient outcome is not fully elucidated. Morphology may be of greater significance …
View article: Object-based feedback attention in convolutional neural networks improves tumour detection in digital pathology
Object-based feedback attention in convolutional neural networks improves tumour detection in digital pathology Open
Human visual attention allows prior knowledge or expectations to influence visual processing, allocating limited computational resources to only that part of the image that are likely to behaviourally important. Here, we present an image r…
View article: Diversity, inclusivity and traceability of mammography datasets used in development of Artificial Intelligence technologies: a systematic review
Diversity, inclusivity and traceability of mammography datasets used in development of Artificial Intelligence technologies: a systematic review Open
View article: Public evidence on AI products for digital pathology
Public evidence on AI products for digital pathology Open
View article: Object-based Feedback Attention in Convolutional Neural Networks Improves Tumour Detection in Digital Pathology
Object-based Feedback Attention in Convolutional Neural Networks Improves Tumour Detection in Digital Pathology Open
Human visual attention allows prior knowledge or expectations to influence visual processing, allocating limited computational resources to only that part of the image that are likely to behaviourally important. Here, we present an image r…
View article: Development of a multi‐scanner facility for data acquisition for digital pathology artificial intelligence
Development of a multi‐scanner facility for data acquisition for digital pathology artificial intelligence Open
Whole slide imaging (WSI) of pathology glass slides using high‐resolution scanners has enabled the large‐scale application of artificial intelligence (AI) in pathology, to support the detection and diagnosis of disease, potentially increas…
View article: Liver-Quant: Feature-Based Image Analysis Toolkit for Automatic Quantification of Metabolic Dysfunction-Associated Steatotic Liver Disease
Liver-Quant: Feature-Based Image Analysis Toolkit for Automatic Quantification of Metabolic Dysfunction-Associated Steatotic Liver Disease Open
Introduction The histological assessment of liver biopsies by pathologists serves as the gold standard for diagnosing metabolic dysfunction-associated steatotic liver disease (MASLD) and staging disease progression. Various machine learnin…
View article: Artificial intelligence in digital pathology: a systematic review and meta-analysis of diagnostic test accuracy
Artificial intelligence in digital pathology: a systematic review and meta-analysis of diagnostic test accuracy Open
Ensuring diagnostic performance of artificial intelligence (AI) before introduction into clinical practice is essential. Growing numbers of studies using AI for digital pathology have been reported over recent years. The aim of this work i…
View article: Pathologists light level preferences using the microscope—study to guide digital pathology display use
Pathologists light level preferences using the microscope—study to guide digital pathology display use Open
View article: Quantitative assessment of H&E staining for pathology: development and clinical evaluation of a novel system
Quantitative assessment of H&E staining for pathology: development and clinical evaluation of a novel system Open
View article: Public evidence on AI products for digital pathology
Public evidence on AI products for digital pathology Open
Background Novel products applying artificial intelligence (AI)-based approaches to digital pathology images have consistently emerged onto the commercial market, touting improvements in diagnostic accuracy, workflow efficiency, and treatm…
View article: Immune subtyping of melanoma whole slide images using multiple instance learning
Immune subtyping of melanoma whole slide images using multiple instance learning Open
View article: The Development and Evaluation of a Convolutional Neural Network for Cutaneous Melanoma Detection in Whole Slide Images
The Development and Evaluation of a Convolutional Neural Network for Cutaneous Melanoma Detection in Whole Slide Images Open
View article: Pathologists light level preferences using the microscope -- a study to guide digital pathology display use
Pathologists light level preferences using the microscope -- a study to guide digital pathology display use Open
There is a paucity of guidelines relating to displays in digital pathology making procurement decisions, and display configuration challenging. Experience suggests pathologists have personal preferences for brightness when using a microsco…
View article: Development of a multi-scanner facility for data acquisition for digital pathology artificial intelligence
Development of a multi-scanner facility for data acquisition for digital pathology artificial intelligence Open
Whole slide imaging (WSI) of pathology glass slides with high-resolution scanners has enabled the large-scale application of artificial intelligence (AI) in pathology, to support the detection and diagnosis of disease, potentially increasi…
View article: The value of standards for health datasets in artificial intelligence-based applications
The value of standards for health datasets in artificial intelligence-based applications Open
View article: Whole-genome sequencing uncovers the genomic determinants of therapeutic resistance to immune checkpoint blockade
Whole-genome sequencing uncovers the genomic determinants of therapeutic resistance to immune checkpoint blockade Open
Checkpoint inhibitors (CPI), ameliorate the anti-tumour response by blocking inhibitory immune checkpoint receptors, and have revolutionised the treatment of advanced cancers. However, the prediction of treatment response is suboptimal, an…
View article: Inalienable data: Ethical imaginaries of de-identified health data ownership
Inalienable data: Ethical imaginaries of de-identified health data ownership Open
View article: Artificial intelligence and medical research databases: ethical review by data access committees
Artificial intelligence and medical research databases: ethical review by data access committees Open