Machine Learning and Real-World Data to Predict Lung Cancer Risk in Routine Care.
Urmila ChandranJenna Marie RepsRobert YangAnil VachaniFabien MaldonadoIftekhar KalsekarPublished in: Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology (2022)
This internally and externally validated real-world data-based lung cancer prediction model is available on an open-source platform for broad sharing and application. Model integration into an EHR system could minimize physician burden by automating identification of high-risk patients.
Keyphrases
- electronic health record
- machine learning
- end stage renal disease
- big data
- healthcare
- ejection fraction
- emergency department
- newly diagnosed
- chronic kidney disease
- primary care
- palliative care
- peritoneal dialysis
- prognostic factors
- high throughput
- patient reported outcomes
- social media
- risk factors
- data analysis
- pain management