AIMC Topic: Pathologists

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Computer-assisted mitotic count using a deep learning-based algorithm improves interobserver reproducibility and accuracy.

Veterinary pathology Dec 30, 2021
The mitotic count (MC) is an important histological parameter for prognostication of malignant neoplasms. However, it has inter- and intraobserver discrepancies due to difficulties in selecting the region of interest (MC-ROI) and in identifying or cl...
Humans Animals Deep Learning Dogs Pathologists Artificial Intelligence Algorithms Reproducibility of Results
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Whole-slide imaging, tissue image analysis, and artificial intelligence in veterinary pathology: An updated introduction and review.

Veterinary pathology Sep 14, 2021
Since whole-slide imaging has been commercially available for over 2 decades, digital pathology has become a constantly expanding aspect of the pathology profession that will continue to significantly impact how pathologists conduct their craft. Whil...
Machine Learning Animals Image Processing, Computer-Assisted Pathologists Humans Artificial Intelligence Pathology, Veterinary
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Skin cancer classification via convolutional neural networks: systematic review of studies involving human experts.

European journal of cancer (Oxford, England : 1990) Sep 8, 2021
BACKGROUND: Multiple studies have compared the performance of artificial intelligence (AI)-based models for automated skin cancer classification to human experts, thus setting the cornerstone for a successful translation of AI-based tools into clinic...
Image Interpretation, Computer-Assisted Automation Pathologists Dermatologists Microscopy Reproducibility of Results Clinical Competence Melanoma Diagnosis, Computer-Assisted Skin Neoplasms Predictive Value of Tests Deep Learning Dermoscopy Biopsy Humans Neural Networks, Computer
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Ethics of AI in Pathology: Current Paradigms and Emerging Issues.

The American journal of pathology Jul 10, 2021
Deep learning has rapidly advanced artificial intelligence (AI) and algorithmic decision-making (ADM) paradigms, affecting many traditional fields of medicine, including pathology, which is a heavily data-centric specialty of medicine. The structured...
Artificial Intelligence Pathologists Risk Stakeholder Participation Pathology Humans
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Grading of invasive breast carcinoma: the way forward.

Virchows Archiv : an international journal of pathology Jul 1, 2021
Histologic grading has been a simple and inexpensive method to assess tumor behavior and prognosis of invasive breast cancer grading, thereby identifying patients at risk for adverse outcomes, who may be eligible for (neo)adjuvant therapies. Histolog...
Breast Neoplasms Neoplasm Grading Pathologists Artificial Intelligence Female Reproducibility of Results Mitosis Humans
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The human-in-the-loop: an evaluation of pathologists' interaction with artificial intelligence in clinical practice.

Histopathology May 30, 2021
AIMS: One of the major drivers of the adoption of digital pathology in clinical practice is the possibility of introducing digital image analysis (DIA) to assist with diagnostic tasks. This offers potential increases in accuracy, reproducibility, and...
Ki-67 Antigen Pathology, Clinical Observer Variation Immunohistochemistry Reproducibility of Results Calibration Breast Neoplasms Biomarkers, Tumor Artificial Intelligence Pathologists Research Design Data Accuracy Retrospective Studies Diagnosis, Computer-Assisted Image Processing, Computer-Assisted Humans
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Independent real-world application of a clinical-grade automated prostate cancer detection system.

The Journal of pathology Apr 27, 2021
Artificial intelligence (AI)-based systems applied to histopathology whole-slide images have the potential to improve patient care through mitigation of challenges posed by diagnostic variability, histopathology caseload, and shortage of pathologists...
Pathologists Biopsy, Large-Core Needle Humans Prostatic Neoplasms Artificial Intelligence Prostate Machine Learning Aged, 80 and over Biopsy Male Aged Middle Aged
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Special Issue on Digital Pathology, Tissue Image Analysis, Artificial Intelligence, and Machine Learning: Approximation of the Effect of Novel Technologies on Toxicologic Pathology.

Toxicologic pathology Apr 12, 2021
For decades, it has been postulated that digital pathology is the future. By now it is safe to say that we are living that future. Digital pathology has expanded into all aspects of pathology, including human diagnostic pathology, veterinary diagnost...
Humans Artificial Intelligence Machine Learning Reproducibility of Results Image Processing, Computer-Assisted Pathologists
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Artificial intelligence (AI) in medicine, current applications and future role with special emphasis on its potential and promise in pathology: present and future impact, obstacles including costs and acceptance among pathologists, practical and philosophical considerations. A comprehensive review.

Diagnostic pathology Mar 17, 2021
BACKGROUND: The role of Artificial intelligence (AI) which is defined as the ability of computers to perform tasks that normally require human intelligence is constantly expanding. Medicine was slow to embrace AI. However, the role of AI in medicine ...
Cost-Benefit Analysis Image Interpretation, Computer-Assisted Practice Patterns, Physicians' Predictive Value of Tests Humans Health Care Costs Reproducibility of Results Pathologists Artificial Intelligence Pathology Attitude of Health Personnel Microscopy Attitude to Computers Health Knowledge, Attitudes, Practice
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Biomarker-Based Classification and Localization of Renal Lesions Using Learned Representations of Histology-A Machine Learning Approach to Histopathology.

Toxicologic pathology Feb 24, 2021
Several deep learning approaches have been proposed to address the challenges in computational pathology by learning structural details in an unbiased way. Transfer learning allows starting from a learned representation of a pretrained model to be di...
Histological Techniques Animals Humans Rats Machine Learning Pathologists Biomarkers
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