AIMC Topic: Cytodiagnosis
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Artificial intelligence technology applications in the pathologic diagnosis of the gastrointestinal tract.
Future oncology (London, England)
Sep 5, 2020
Artificial intelligence (AI) is a complex technology with a steady flow of new applications, including in the pathology laboratory. Applications of AI in pathology are scarce but increasing; they are based on complex software-based machine learning w...
The artificial intelligence-assisted cytology diagnostic system in large-scale cervical cancer screening: A population-based cohort study of 0.7 million women.
Cancer medicine
Jul 22, 2020
BACKGROUND: Adequate cytology is limited by insufficient cytologists in a large-scale cervical cancer screening. We aimed to develop an artificial intelligence (AI)-assisted cytology system in cervical cancer screening program.
Review of different platforms to perform rapid onsite evaluation via telecytology.
Cytopathology : official journal of the British Society for Clinical Cytology
Jul 5, 2020
There is increased utilisation of cytopathology to provide a rapid onsite evaluation (ROSE) of fine needle aspiration and touch preparations of small biopsies. A well-executed ROSE procedure can significantly impact the diagnostic quality and appropr...
The cytopathologist's role in developing and evaluating artificial intelligence in cytopathology practice.
Cytopathology : official journal of the British Society for Clinical Cytology
Feb 27, 2020
Artificial intelligence (AI) technologies have the potential to transform cytopathology practice, and it is important for cytopathologists to embrace this and place themselves at the forefront of implementing these technologies in cytopathology. This...
Application of a machine learning algorithm to predict malignancy in thyroid cytopathology.
Cancer cytopathology
Feb 3, 2020
BACKGROUND: The Bethesda System for Reporting Thyroid Cytopathology (TBSRTC) comprises 6 categories used for the diagnosis of thyroid fine-needle aspiration biopsy (FNAB). Each category has an associated risk of malignancy, which is important in the ...
CytoProcessorTM: A New Cervical Cancer Screening System for Remote Diagnosis.
Acta cytologica
Mar 28, 2019
BACKGROUND: Current automated cervical cytology screening systems still heavily depend on manipulation of glass slides. We developed a new system called CytoProcessorTM (DATEXIM, Caen, France), which increases sensitivity and takes advantage of virtu...
Artificial intelligence in cytopathology: a review of the literature and overview of commercial landscape.
Journal of the American Society of Cytopathology
Mar 25, 2019
Artificial intelligence (AI) has made impressive strides recently in interpreting complex images, thanks to improvements in deep learning techniques and increasing computational power. Researchers have started applying these advanced techniques to pa...
Automating the Paris System for urine cytopathology-A hybrid deep-learning and morphometric approach.
Cancer cytopathology
Jan 31, 2019
BACKGROUND: The Paris System for Urine Cytopathology (the Paris System) has succeeded in making the analysis of liquid-based urine preparations more reproducible. Any algorithm seeking to automate this system must accurately estimate the nuclear-to-c...
Determination of appropriate urine volume cutoff values for voided urine specimens to assess adequacy.
Journal of the American Society of Cytopathology
Nov 7, 2018
INTRODUCTION: Incorporating urine volume into adequacy assessment was recommended by The Paris System for Reporting Urinary Cytology. The concept was relatively new, however, and supportive studies were sparse. We accordingly aimed to determine the r...
Convolutional Neural Network for Histopathological Analysis of Osteosarcoma.
Journal of computational biology : a journal of computational molecular cell biology
Oct 30, 2017
Pathologists often deal with high complexity and sometimes disagreement over osteosarcoma tumor classification due to cellular heterogeneity in the dataset. Segmentation and classification of histology tissue in H&E stained tumor image datasets is a ...
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