Temporally integrated framework for treatment intervals (TIFTI): A framework for extracting drug intervals from longitudinal clinic notes Published December 2018 Citation Agrawal, M, Adams, G, Nussbaum, NC, Birnbaum, B. . Machine Learning for Health (ML4H) Workshop. . https://arxiv.org/pdf/1811.12793.pdf Authors:Agrawal, M, Adams, G, Nussbaum, NC, Birnbaum, B Sources:Machine Learning for Health (ML4H) Workshop Share Posted inPublicationsMachine learningMethodology More publicationsISPORApril 2026From real-world data (RWD) to digital twins: building models for patient-level counterfactual prediction in oncologyGriffith S, Manfredonia J, Ricottone M, et al.Publication summaryPublicationsMachine learningNon-small cell lung cancerArtificial intelligenceISPORApril 2026Assessing quality of a LLM-derived prostate cancer (PC) real-world dataset: an application of the validation of accuracy for LLM/ML-extracted information and data (VALID) frameworkWard PJ, Qian Y, Hankinson EA, Dolor A, Estevez M, et al.Publication summaryPublicationsMachine learningProstate cancerArtificial intelligenceISPORApril 2026Evaluating model performance for between-country survival transportabilityAli MS, Pittell H, Horne E, Mpofu P, Zhang Q, Adamson B, et al.Publication summaryPublicationsMethodologyMultiple myeloma