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Pathologists

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Comparing deep learning and pathologist quantification of cell-level PD-L1 expression in non-small cell lung cancer whole-slide images.

Scientific reports
Programmed death-ligand 1 (PD-L1) expression is currently used in the clinic to assess eligibility for immune-checkpoint inhibitors via the tumor proportion score (TPS), but its efficacy is limited by high interobserver variability. Multiple papers h...

DiagSet: a dataset for prostate cancer histopathological image classification.

Scientific reports
Cancer diseases constitute one of the most significant societal challenges. In this paper, we introduce a novel histopathological dataset for prostate cancer detection. The proposed dataset, consisting of over 2.6 million tissue patches extracted fro...

Closing the loop - the role of pathologists in digital and computational pathology research.

The journal of pathology. Clinical research
An increasing number of manuscripts related to digital and computational pathology are being submitted to The Journal of Pathology: Clinical Research as part of the continuous evolution from digital imaging and algorithm-based digital pathology to co...

Critical evaluation of artificial intelligence as a digital twin of pathologists for prostate cancer pathology.

Scientific reports
Prostate cancer pathology plays a crucial role in clinical management but is time-consuming. Artificial intelligence (AI) shows promise in detecting prostate cancer and grading patterns. We tested an AI-based digital twin of a pathologist, vPatho, on...

Scoring PD-L1 Expression in Urothelial Carcinoma: An International Multi-Institutional Study on Comparison of Manual and Artificial Intelligence Measurement Model (AIM-PD-L1) Pathology Assessments.

Virchows Archiv : an international journal of pathology
Assessing programmed death ligand 1 (PD-L1) expression on tumor cells (TCs) using Food and Drug Administration-approved, validated immunoassays can guide the use of immune checkpoint inhibitor (ICI) therapy in cancer treatment. However, substantial i...

Artificial Intelligence Helps Pathologists Increase Diagnostic Accuracy and Efficiency in the Detection of Breast Cancer Lymph Node Metastases.

The American journal of surgical pathology
The detection of lymph node metastases is essential for breast cancer staging, although it is a tedious and time-consuming task where the sensitivity of pathologists is suboptimal. Artificial intelligence (AI) can help pathologists detect lymph node ...

A pathologist-AI collaboration framework for enhancing diagnostic accuracies and efficiencies.

Nature biomedical engineering
In pathology, the deployment of artificial intelligence (AI) in clinical settings is constrained by limitations in data collection and in model transparency and interpretability. Here we describe a digital pathology framework, nuclei.io, that incorpo...

A Deep Learning-Based Assay for Programmed Death Ligand 1 Immunohistochemistry Scoring in Non-Small Cell Lung Carcinoma: Does it Help Pathologists Score?

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Several studies have developed various artificial intelligence (AI) models for immunohistochemical analysis of programmed death ligand 1 (PD-L1) in patients with non-small cell lung carcinoma; however, none have focused on specific ways by which AI-a...

Democratizing Artificial Intelligence in Anatomic Pathology.

Archives of pathology & laboratory medicine
CONTEXT.—: Artificial intelligence is a transforming technology for anatomic pathology. Involvement within the workforce will foster support for algorithm development and implementation.

General Applicability of Existing College of American Pathologists Accreditation Requirements to Clinical Implementation of Machine Learning-Based Methods in Molecular Oncology Testing.

Archives of pathology & laboratory medicine
CONTEXT.—: The College of American Pathologists (CAP) accreditation requirements for clinical laboratory testing help ensure laboratories implement and maintain systems and processes that are associated with quality. Machine learning (ML)-based model...