Abdalla, Mohamed

Empirical data drift detection experiments on real-world medical imaging data

Kore, A., Abbasi Bavil, E., Subasri, V., Abdalla, M., Fine, B., Dolatabadi, E., & Abdalla, M. (2024) · Nature Communications

Data Stream Mining TechniquesArtificial Intelligence in Healthcare and Education

Cited by 124

Hurtful words: quantifying biases in clinical contextual word embeddings

Zhang, H., Lu, A. X., Abdalla, M., McDermott, M., & Ghassemi, M. (2020) · Proceedings of the ACM Conference on Health, Inference, and Learning

Machine Learning in HealthcareEthics and Social Impacts of AI

Cited by 122

Hurtful Words: Quantifying Biases in Clinical Contextual Word Embeddings

Zhang, H., Lu, A. X., Abdalla, M., McDermott, M., & Ghassemi, M. (2020) · arXiv

Machine Learning in HealthcareEthics and Social Impacts of AI

Cited by 37

The Subgroup Imperative: Chest Radiograph Classifier Generalization Gaps in Patient, Setting, and Pathology Subgroups

Ahluwalia, M., Abdalla, M., Sanayei, J., Seyyed-Kalantari, L., Hussain, M., Ali, A., & Fine, B. (2023) · Radiology: Artificial Intelligence

Artificial Intelligence in Healthcare and EducationCOVID-19 diagnosis using AI

Cited by 26

Hurdles to Artificial Intelligence Deployment: Noise in Schemas and “Gold” Labels

Abdalla, M., & Fine, B. (2023) · Radiology: Artificial Intelligence

Artificial Intelligence in Healthcare and EducationCOVID-19 diagnosis using AI

Cited by 24

Beyond a Million Tokens: Benchmarking and Enhancing Long-Term Memory in LLMs

Tavakoli, M., Salemi, A., Ye, C., Abdalla, M., Zamani, H., & Mitchell, J. R. (2025) · arXiv

Topic ModelingSpeech and dialogue systems

Cited by 0