AIMC Topic: Pathology
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What Works Where and How for Uptake and Impact of Artificial Intelligence in Pathology: Review of Theories for a Realist Evaluation.
Journal of medical Internet research
Apr 24, 2023
BACKGROUND: There is increasing interest in the use of artificial intelligence (AI) in pathology to increase accuracy and efficiency. To date, studies of clinicians' perceptions of AI have found only moderate acceptability, suggesting the need for fu...
Predictive uncertainty estimation for out-of-distribution detection in digital pathology.
Medical image analysis
Oct 17, 2022
Machine learning model deployment in clinical practice demands real-time risk assessment to identify situations in which the model is uncertain. Once deployed, models should be accurate for classes seen during training while providing informative est...
Recommendations on compiling test datasets for evaluating artificial intelligence solutions in pathology.
Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Sep 10, 2022
Artificial intelligence (AI) solutions that automatically extract information from digital histology images have shown great promise for improving pathological diagnosis. Prior to routine use, it is important to evaluate their predictive performance ...
Non-invasive scoring of cellular atypia in keratinocyte cancers in 3D LC-OCT images using Deep Learning.
Scientific reports
Jan 10, 2022
Diagnosis based on histopathology for skin cancer detection is today's gold standard and relies on the presence or absence of biomarkers and cellular atypia. However it suffers drawbacks: it requires a strong expertise and is time-consuming. Moreover...
Digital pathology and artificial intelligence in translational medicine and clinical practice.
Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Oct 5, 2021
Traditional pathology approaches have played an integral role in the delivery of diagnosis, semi-quantitative or qualitative assessment of protein expression, and classification of disease. Technological advances and the increased focus on precision ...
Quick Annotator: an open-source digital pathology based rapid image annotation tool.
The journal of pathology. Clinical research
Jul 19, 2021
Image-based biomarker discovery typically requires accurate segmentation of histologic structures (e.g. cell nuclei, tubules, and epithelial regions) in digital pathology whole slide images (WSIs). Unfortunately, annotating each structure of interest...
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...
Applications of machine learning in the chemical pathology laboratory.
Journal of clinical pathology
Jun 11, 2021
Machine learning (ML) is an area of artificial intelligence that provides computer programmes with the capacity to autodidact and learn new skills from experience, without continued human programming. ML algorithms can analyse large data sets quickly...
Histopathological characteristics and artificial intelligence for predicting tumor mutational burden-high colorectal cancer.
Journal of gastroenterology
Apr 28, 2021
BACKGROUND: Tumor mutational burden-high (TMB-H), which is detected with gene panel testing, is a promising biomarker for immune checkpoint inhibitors (ICIs) in colorectal cancer (CRC). However, in clinical practice, not every patient is tested for T...
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