Low-cost method for the diagnosis of chronic obstructive pulmonary disease using ensemble ml model
AssigneesAdvait Achanta, Suhaas Devalapally
InventorsAdvait Achanta, Suhaas Devalapally
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Abstract
The present invention is related to a simple, low-cost method for the early diagnosis of COPD in patients using an ensemble ML model residing on cloud or server. A web-based application accessed on a smart phone or a computing device through internet facilitates the entry of patient characteristics such as age, gender, smoking habits, hypertension, pack history, etc. and clinical features such as FEV, MWT and CO levels in the exhaled breath of patients. The patient characteristics is used with the ensemble ML model to predict the severity of COPD disease. The web application also enables sending the results to a receiver via email or text message for further action.
Claims6
A method for the diagnosis of chronic obstructive pulmonary disease (COPD) in patients with respiratory conditions comprising:
- obtaining patient characteristics and clinical features;
- feeding said patient characteristics and clinical features into a web application on a computing device;
- using an ensemble machine learning (ML) model residing on the cloud;
- and
- displaying the severity of COPD on said computing device,
- wherein said ensemble ML model is a combination of Decision Tree, Random Forest and Gradient Boosting models.
Dependencies are inferred from the claim text.