Arıyan Teimoori

Hierarchical temporal transformer for cancer grade prediction and cross cancer transfer learning from pathology reports

The paper introduces HTT, a model that improves cancer grade prediction from pathology reports by incorporating temporal information and cross-cancer transfer learning, achieving high AUROC scores on unseen cancer types.

Medicament identity rather than total loading governs the morphology of electrospun poly(vinylpyrrolidone) nanofibers for regenerative endodontics: a machine learning analysis of a failure-inclusive dataset

The paper uses machine learning to analyze a dataset of electrospun nanofibers, finding that medicament identity, not total loading, better predicts fiber morphology in regenerative endodontics.