| アブストラクト | Oesophago-gastric cancer is difficult to diagnose in the early stages given its typical non-specific initial manifestation. We hypothesise that machine learning can improve upon the diagnostic performance of current primary care risk-assessment tools by using advanced analytical techniques to exploit the wealth of evidence available in the electronic health record. We used a primary care electronic health record dataset derived from the UK General Practice Research Database (7471 cases; 32,877 controls) and developed five probabilistic machine learning classifiers: Support Vector Machine, Random Forest, Logistic Regression, Naive Bayes, and Extreme Gradient Boosted Decision Trees. Features included basic demographics, symptoms, and lab test results. The Logistic Regression, Support Vector Machine, and Extreme Gradient Boosted Decision Tree models achieved the highest performance in terms of accuracy and AUROC (0.89 accuracy, 0.87 AUROC), outperforming a current UK oesophago-gastric cancer risk-assessment tool (ogRAT). Machine learning also identified more cancer patients than the ogRAT: 11.0% more with little to no effect on false positives, or up to 25.0% more with a slight increase in false positives (for Logistic Regression, results threshold-dependent). Feature contribution estimates and individual prediction explanations indicated clinical relevance. We conclude that machine learning could improve primary care cancer risk-assessment tools, potentially helping clinicians to identify additional cancer cases earlier. This could, in turn, improve survival outcomes. |
|---|
| ジャーナル名 | Cancers |
|---|
| Pubmed追加日 | 2022/10/28 |
|---|
| 投稿者 | Briggs, Emma; de Kamps, Marc; Hamilton, Willie; Johnson, Owen; McInerney, Ciaran D; Neal, Richard D |
|---|
| 組織名 | School of Computing, University of Leeds, Leeds LS2 9JT, UK.;Leeds Institute for Data Analytics, University of Leeds, Leeds LS2 9NL, UK.;The Alan Turing Institute, London NW1 2DB, UK.;Department of Health and Community Sciences, University of Exeter, Exeter EX1;2LU, UK.;Academic Unit of Primary Medical Care, University of Sheffield, Sheffield S10;2TN, UK. |
|---|
| Pubmed リンク | https://www.ncbi.nlm.nih.gov/pubmed/36291807/ |
|---|
