Sara Ketabi

According to our database, Sara Ketabi authored at least 8 papers between 2022 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2026

Exploring Radiologists' Expectations of Explainable Machine Learning Models in Medical Image Analysis.

Sara Ketabi, Matthias W. Wagner, Birgit Betina Ertl-Wagner, Greg A. Jamieson, Farzad Khalvati

CoRR, April, 2026

2025

ProtoTopic: Prototypical Network for Few-Shot Medical Topic Modeling.

Martin Licht, Sara Ketabi, Farzad Khalvati

CoRR, October, 2025

Bridging Electronic Health Records and Clinical Texts: Contrastive Learning for Enhanced Clinical Tasks.

Sara Ketabi, Dhanesh Ramachandram

CoRR, May, 2025

2024

Tumor Location-weighted MRI-Report Contrastive Learning: A Framework for Improving the Explainability of Pediatric Brain Tumor Diagnosis.

Sara Ketabi, Matthias W. Wagner, Cynthia Hawkins, Uri Tabori, Birgit Betina Ertl-Wagner, Farzad Khalvati

CoRR, 2024

Improving Interpretability of Radiology Report-based Pediatric Brain Tumor Pathology Classification and Key-phrases Extraction Using Large Language Models.

Chen Zhao, Kareem Kudus, Sara Ketabi, Khashayar Namdar, Matthias W. Wagner, Birgit B. Ertl-Wagner, Farzad Khalvati

Proceedings of the IEEE EMBS International Conference on Biomedical and Health Informatics, 2024

2023

Multimodal Learning for Improving Performance and Explainability of Chest X-Ray Classification.

Sara Ketabi, Pranav Agnihotri, Hamed Zakeri, Khashayar Namdar, Farzad Khalvati

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023 Workshops, 2023

2022

Using Multi-modal Data for Improving Generalizability and Explainability of Disease Classification in Radiology.

Pranav Agnihotri, Sara Ketabi, Khashayar Namdar, Farzad Khalvati

CoRR, 2022

Improving Disease Classification Performance and Explainability of Deep Learning Models in Radiology with Heatmap Generators.

Akino Watanabe, Sara Ketabi, Khashayar Namdar, Farzad Khalvati

CoRR, 2022