Sökning: id:"swepub:oai:DiVA.org:uu-440460" >
Point-of-Care Digit...
Point-of-Care Digital Cytology With Artificial Intelligence for Cervical Cancer Screening in a Resource-Limited Setting
-
- Holmström, Oscar (författare)
- Univ Helsinki, Inst Mol Med Finland, Helsinki, Finland.
-
- Linder, Nina (författare)
- Uppsala universitet,Internationell barnhälsa och nutrition,Univ Helsinki, Inst Mol Med Finland, Helsinki, Finland.
-
- Kaingu, Harrison (författare)
- Kinondo Kwetu Hlth Serv Clin, Kinondo, Kenya.
-
visa fler...
-
- Mbuuko, Ngali (författare)
- Kinondo Kwetu Hlth Serv Clin, Kinondo, Kenya.
-
- Mbete, Jumaa (författare)
- Kinondo Kwetu Hlth Serv Clin, Kinondo, Kenya.
-
- Kinyua, Felix (författare)
- Kinondo Kwetu Hlth Serv Clin, Kinondo, Kenya.
-
- Törnquist, Sara (författare)
- Karolinska Inst, Dept Global Publ Hlth, S-17177 Stockholm, Sweden.
-
- Muinde, Martin (författare)
- Kinondo Kwetu Hlth Serv Clin, Kinondo, Kenya.
-
- Krogerus, Leena (författare)
- Helsinki Univ Cent Hosp Lab HUSLAB, Helsinki & Uusimaa Hosp Dist, HUS Diagnost Ctr, Helsinki, Finland.
-
- Lundin, Mikael (författare)
- Univ Helsinki, Inst Mol Med Finland, Helsinki, Finland.
-
- Diwan, Vinod (författare)
- Karolinska Institutet
-
- Lundin, Johan (författare)
- Karolinska Institutet
-
visa färre...
-
Univ Helsinki, Inst Mol Med Finland, Helsinki, Finland Internationell barnhälsa och nutrition (creator_code:org_t)
- 2021-03-17
- 2021
- Engelska.
-
Ingår i: JAMA Network Open. - : American Medical Association (AMA). - 2574-3805. ; 4:3
- Relaterad länk:
-
https://jamanetwork....
-
visa fler...
-
https://urn.kb.se/re...
-
https://doi.org/10.1...
-
http://kipublication...
-
visa färre...
Abstract
Ämnesord
Stäng
- Importance: Cervical cancer is highly preventable but remains a common and deadly cancer in areas without screening programs. The creation of a diagnostic system to digitize Papanicolaou test samples and analyze them using a cloud-based deep learning system (DLS) may provide needed cervical cancer screening to resource-limited areas.Objective: To determine whether artificial intelligence-supported digital microscopy diagnostics can be implemented in a resource-limited setting and used for analysis of Papanicolaou tests.Design, Setting, and Participants: In this diagnostic study, cervical smears from 740 HIV-positive women aged between 18 and 64 years were collected between September 1, 2018, and September 30, 2019. The smears were digitized with a portable slide scanner, uploaded to a cloud server using mobile networks, and used to train and validate a DLS for the detection of atypical cervical cells. This single-center study was conducted at a local health care center in rural Kenya.Exposures: Detection of squamous cell atypia in the digital samples by analysis with the DLS.Main Outcomes and Measures: The accuracy of the DLS in the detection of low- and high-grade squamous intraepithelial lesions in Papanicolaou test whole-slide images.Results: Papanicolaou test results from 740 HIV-positive women (mean [SD] age, 41.8 [10.3] years) were collected. The DLS was trained using 350 whole-slide images and validated on 361 whole-slide images (average size, 100 387 x 47 560 pixels). For detection of cervical cellular atypia, sensitivities were 95.7% (95% CI, 85.5%-99.5%) and 100% (95% CI, 82.4%-100%), and specificities were 84.7% (95% CI, 80.2%-88.5%) and 78.4% (95% CI, 73.6%-82.4%), compared with the pathologist assessment of digital and physical slides, respectively. Areas under the receiver operating characteristic curve were 0.94 and 0.96, respectively. Negative predictive values were high (99%-100%), and accuracy was high, particularly for the detection of high-grade lesions. Interrater agreement was substantial compared with the pathologist assessment of digital slides (kappa = 0.72) and fair compared with the assessment of glass slides (kappa = 0.36). No samples that were classified as high grade by manual sample analysis had false-negative assessments by the DLS.Conclusions and Relevance: In this study, digital microscopy with artificial intelligence was implemented at a rural clinic and used to detect atypical cervical smears with a high sensitivity compared with visual sample analysis.
Ämnesord
- MEDICIN OCH HÄLSOVETENSKAP -- Klinisk medicin -- Cancer och onkologi (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Clinical Medicine -- Cancer and Oncology (hsv//eng)
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
Hitta via bibliotek
Till lärosätets databas
- Av författaren/redakt...
-
Holmström, Oscar
-
Linder, Nina
-
Kaingu, Harrison
-
Mbuuko, Ngali
-
Mbete, Jumaa
-
Kinyua, Felix
-
visa fler...
-
Törnquist, Sara
-
Muinde, Martin
-
Krogerus, Leena
-
Lundin, Mikael
-
Diwan, Vinod
-
Lundin, Johan
-
visa färre...
- Om ämnet
-
- MEDICIN OCH HÄLSOVETENSKAP
-
MEDICIN OCH HÄLS ...
-
och Klinisk medicin
-
och Cancer och onkol ...
- Artiklar i publikationen
-
JAMA Network Ope ...
- Av lärosätet
-
Uppsala universitet
-
Karolinska Institutet