Publications & White Papers

Validation of LungFlag™ Prediction Model Using Electronic Medical Records (EMR) on Taiwan Data Presented at the World Conference on Lung Cancer

Budget impact model of LungFlag™, a predictive risk model for lung cancer screening

Development and Validation of a Machine-learning Prediction Model to Improve Abdominal Aortic Aneurysm Screening

Use of the Predictive Risk Model, LungFlag™ for Lung Cancer Screening in a Spanish Reference Center: A Cost-effectiveness Analysis.

Cost-effectiveness of a machine learning risk prediction model (LungFlag™) in the selection of high-risk individuals for non-small cell lung cancer screening in Spain

Improved Efficiency with LungFlag™ vs. Opportunistic Selection in a Theoretical East Asian Lung Cancer Screening Program

LungFlag™, a Machine-Learning (ML) Personalized Tool for Assessing Pulmonary Complications a Community Setting, Demonstrates Comparable Performance in Flagging Non-Small Cell Lung Cancer.

Computer-assisted Flagging of Never Smokers at High Risk of NSCLC in a Large US-based HMO using the LungFlag Model

Flagging high-risk individuals with an ML model improves NSCLC early detection in a USPSTF-eligible population

Prediction of influenza complications: Development and validation of a machine learning prediction model to improve and expand the identification of vaccine-hesitant patients at risk of severe influenza complications

Geisinger, Medial EarlySign find algorithm can detect patients at high risk for colorectal cancer

Collaboration to Improve Colorectal Cancer Screening Using Machine Learning

Validation of LungFlag™ Prediction Model Using Electronic Medical Records (EMR) on Taiwan Data Presented at the World Conference on Lung Cancer

Budget impact model of LungFlag™, a predictive risk model for lung cancer screening

Development and Validation of a Machine-learning Prediction Model to Improve Abdominal Aortic Aneurysm Screening

Use of the Predictive Risk Model, LungFlag™ for Lung Cancer Screening in a Spanish Reference Center: A Cost-effectiveness Analysis.

Cost-effectiveness of a machine learning risk prediction model (LungFlag™) in the selection of high-risk individuals for non-small cell lung cancer screening in Spain

Improved Efficiency with LungFlag™ vs. Opportunistic Selection in a Theoretical East Asian Lung Cancer Screening Program

LungFlag™, a Machine-Learning (ML) Personalized Tool for Assessing Pulmonary Complications a Community Setting, Demonstrates Comparable Performance in Flagging Non-Small Cell Lung Cancer.

Computer-assisted Flagging of Never Smokers at High Risk of NSCLC in a Large US-based HMO using the LungFlag Model

Flagging high-risk individuals with an ML model improves NSCLC early detection in a USPSTF-eligible population

Prediction of influenza complications: Development and validation of a machine learning prediction model to improve and expand the identification of vaccine-hesitant patients at risk of severe influenza complications

Geisinger, Medial EarlySign find algorithm can detect patients at high risk for colorectal cancer

Collaboration to Improve Colorectal Cancer Screening Using Machine Learning