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Estimating diagnost...
Estimating diagnostic uncertainty in artificial intelligence assisted pathology using conformal prediction
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- Olsson, Henrik (author)
- Karolinska Institutet
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- Kartasalo, Kimmo (author)
- Karolinska Institutet
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Mulliqi, Nita (author)
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- Capuccini, Marco (author)
- Uppsala universitet,Institutionen för farmaceutisk biovetenskap
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Ruusuvuori, Pekka (author)
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Samaratunga, Hemamali (author)
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Delahunt, Brett (author)
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- Lindskog, Cecilia (author)
- Uppsala universitet,Cancerprecisionsmedicin
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Janssen, Emiel A. M. (author)
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Blilie, Anders (author)
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- Egevad, Lars (author)
- Karolinska Institutet
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- Spjuth, Ola, Professor, 1977- (author)
- Uppsala universitet,Institutionen för farmaceutisk biovetenskap
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- Eklund, Martin (author)
- Karolinska Institutet
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(creator_code:org_t)
- 2022-12-15
- 2022
- English.
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In: Nature Communications. - : Springer Nature. - 2041-1723. ; 13:1
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Abstract
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- Unreliable predictions can occur when an artificial intelligence (AI) system is presented with data it has not been exposed to during training. We demonstrate the use of conformal prediction to detect unreliable predictions, using histopathological diagnosis and grading of prostate biopsies as example. We digitized 7788 prostate biopsies from 1192 men in the STHLM3 diagnostic study, used for training, and 3059 biopsies from 676 men used for testing. With conformal prediction, 1 in 794 (0.1%) predictions is incorrect for cancer diagnosis (compared to 14 errors [2%] without conformal prediction) while 175 (22%) of the predictions are flagged as unreliable when the AI-system is presented with new data from the same lab and scanner that it was trained on. Conformal prediction could with small samples (N = 49 for external scanner, N = 10 for external lab and scanner, and N = 12 for external lab, scanner and pathology assessment) detect systematic differences in external data leading to worse predictive performance. The AI-system with conformal prediction commits 3 (2%) errors for cancer detection in cases of atypical prostate tissue compared to 44 (25%) without conformal prediction, while the system flags 143 (80%) unreliable predictions. We conclude that conformal prediction can increase patient safety of AI-systems.
Subject headings
- MEDICIN OCH HÄLSOVETENSKAP -- Medicinska och farmaceutiska grundvetenskaper -- Cell- och molekylärbiologi (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Basic Medicine -- Cell and Molecular Biology (hsv//eng)
Keyword
- Biology with specialization in Molecular Biology
- Biologi med inriktning mot molekylärbiologi
Publication and Content Type
- ref (subject category)
- art (subject category)
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- By the author/editor
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Olsson, Henrik
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Kartasalo, Kimmo
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Mulliqi, Nita
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Capuccini, Marco
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Ruusuvuori, Pekk ...
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Samaratunga, Hem ...
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show more...
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Delahunt, Brett
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Lindskog, Cecili ...
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Janssen, Emiel A ...
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Blilie, Anders
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Egevad, Lars
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Spjuth, Ola, Pro ...
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Eklund, Martin
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- About the subject
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- MEDICAL AND HEALTH SCIENCES
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MEDICAL AND HEAL ...
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and Basic Medicine
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and Cell and Molecul ...
- Articles in the publication
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Nature Communica ...
- By the university
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Uppsala University
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Karolinska Institutet