Patient classification of two-week wait referrals for suspected head and neck cancer: a machine learning approach
| Autor: | J W Moor, J Edwards, Vinidh Paleri |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Referral
business.industry Head and neck cancer Cancer 030208 emergency & critical care medicine General Medicine Machine learning computer.software_genre medicine.disease Logistic regression 03 medical and health sciences Statistical classification 0302 clinical medicine Otorhinolaryngology Patient classification medicine Artificial intelligence Medical diagnosis 030223 otorhinolaryngology business computer |
| Zdroj: | The Journal of laryngology and otology. 133(10) |
| ISSN: | 1748-5460 0022-2151 |
| Popis: | BackgroundMachine learning algorithms could potentially be used to classify patients referred on the two-week wait pathway for suspected head and neck cancer. Patients could be classified into ‘predicted cancer’ or ‘predicted non-cancer’ groups.MethodsA variety of machine learning algorithms were assessed using the clinical data of 5082 patients. These patients had previously been referred via the two-week wait pathway for suspected head and neck cancer to two separate tertiary referral centres in the UK. Outcomes from machine learning classification were analysed in comparison to known clinical diagnoses.ResultsVariational logistic regression was the most clinically useful technique of those chosen to perform the analysis and patient classification; the proportion of patients correctly classified as having ‘non-cancer’ was 25.8 per cent, with a false negative rate of 1 out of 1000.ConclusionMachine learning algorithms can accurately and effectively classify patients referred with suspected head and neck cancer symptoms. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|