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Explainable Artific...
Explainable Artificial Neural Network for Recurrent Venous Thromboembolism Based on Plasma Proteomics
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Razzaq, M. (author)
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Goumidi, L. (author)
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- Iglesias, Maria Jesus (author)
- KTH,Science for Life Laboratory, SciLifeLab,Cellulär och klinisk proteomik,Department of Clinical Medicine, Faculty of Health Science, The Arctic University of Tromsö, Tromsö, Norway
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Munsch, G. (author)
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Bruzelius, M. (author)
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Ibrahim-Kosta, M. (author)
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- Butler, Lynn M. (author)
- KTH,Science for Life Laboratory, SciLifeLab,Cellulär och klinisk proteomik,Department of Clinical Medicine, Faculty of Health Science, The Arctic University of Tromsö, Tromsö, Norway
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- Odeberg, Jacob, Professor, 1963- (author)
- KTH,Science for Life Laboratory, SciLifeLab,Proteinvetenskap,Department of Clinical Medicine, Faculty of Health Science, The Arctic University of Tromsö, Tromsö, Norway
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Morange, P. -E (author)
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Tregouet, D. A. (author)
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(creator_code:org_t)
- 2021-09-13
- 2021
- English.
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In: Computational Methods in Systems Biology19th International Conference, CMSB 2021, Bordeaux, France, September 22–24, 2021, Proceedings. - Cham : Springer Science and Business Media Deutschland GmbH. ; , s. 108-121
- Related links:
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
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- Venous thromboembolism (VTE) is the third most common cardiovascular disease, affecting ∼ 1,000,000 individuals each year in Europe. VTE is characterized by an annual recurrent rate of ∼ 6%, and ∼ 30% of patients with unprovoked VTE will face a recurrent event after a six-month course of anticoagulant treatment. Even if guidelines recommend life-long treatment for these patients, about ∼ 70% of them will never experience a recurrence and will receive unnecessary lifelong anti-coagulation that is associated with increased risk of bleeding and is highly costly for the society. There is then urgent need to identify biomarkers that could distinguish VTE patients with high risk of recurrence from low-risk patients. Capitalizing on a sample of 913 patients followed up for the risk of VTE recurrence during a median of ∼ 10 years and profiled for 376 plasma proteomic antibodies, we here develop an artificial neural network (ANN) based strategy to identify a proteomic signature that helps discriminating patients at low and high risk of recurrence. In a first stage, we implemented a Repeated Editing Nearest Neighbors algorithm to select a homogeneous sub-sample of VTE patients. This sub-sample was then split in a training and a testing sets. The former was used for training our ANN, the latter for testing its discriminatory properties. In the testing dataset, our ANN led to an accuracy of 0.86 that compared to an accuracy of 0.79 as provided by a random forest classifier. We then applied a Deep Learning Important FeaTures (DeepLIFT) – based approach to identify the variables that contribute the most to the ANN predictions. In addition to sex, the proposed DeepLIFT strategy identified 6 important proteins (DDX1, HTRA3, LRG1, MAST2, NFATC4 and STXBP5) whose exact roles in the etiology of VTE recurrence now deserve further experimental validations.
Subject headings
- MEDICIN OCH HÄLSOVETENSKAP -- Klinisk medicin -- Kardiologi (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Clinical Medicine -- Cardiac and Cardiovascular Systems (hsv//eng)
- MEDICIN OCH HÄLSOVETENSKAP -- Klinisk medicin -- Hematologi (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Clinical Medicine -- Hematology (hsv//eng)
Keyword
- Artificial neural network
- Imbalanced
- Interpretation
- Proteomics
- Thrombosis
- Classification (of information)
- Decision trees
- Molecular biology
- Patient treatment
- Proteins
- Recurrent neural networks
- Statistical tests
- Anti-coagulation
- Bleedings
- Cardiovascular disease
- Important features
- Recurrent events
- Sub-samples
- Venous thromboembolism
- Diseases
Publication and Content Type
- ref (subject category)
- kon (subject category)
To the university's database
- By the author/editor
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Razzaq, M.
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Goumidi, L.
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Iglesias, Maria ...
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Munsch, G.
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Bruzelius, M.
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Ibrahim-Kosta, M ...
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show more...
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Butler, Lynn M.
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Odeberg, Jacob, ...
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Morange, P. -E
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Tregouet, D. A.
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show less...
- About the subject
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- MEDICAL AND HEALTH SCIENCES
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MEDICAL AND HEAL ...
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and Clinical Medicin ...
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and Cardiac and Card ...
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- MEDICAL AND HEALTH SCIENCES
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MEDICAL AND HEAL ...
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and Clinical Medicin ...
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and Hematology
- Articles in the publication
- Computational Me ...
- By the university
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Royal Institute of Technology