7 citations · 18 across the 8 of their papers we have counts for
11 papers
Memorilla: Latent Semantic Memory for LLMs
Adibvafa Fallahpour, Parsa Idehpour, Vignesh Kothapalli +4
Memory enables large language models (LLMs) to use information beyond their parameters, such as past user conversations, long documents, or an agent's earlier actions. For a frozen…
OpenMedReason: Scientific Reasoning Supervision for Medical Vision-Language Models
Negin Baghbanzadeh, Pritam Sarkar, Michael Colacci +6
High-stakes clinical use of large vision-language models (LVLMs) requires reasoning that is grounded in visual evidence and clinical knowledge, not just correct final answers. We i…
EchoJEPA: A Latent Predictive Foundation Model for Echocardiography
Alif Munim, Adibvafa Fallahpour, Teodora Szasz +9
Foundation models for echocardiography often struggle to disentangle anatomical signal from the stochastic speckle and acquisition artifacts inherent to ultrasound. We present Echo…
dnaHNet: A Scalable and Hierarchical Foundation Model for Genomic Sequence Learning
Arnav Shah, Junzhe Li, Parsa Idehpour +7
Genomic foundation models have the potential to decode DNA syntax, yet face a fundamental tradeoff in their input representation. Standard fixed-vocabulary tokenizers fragment biol…
An Investigation of Memorization Risk in Healthcare Foundation Models
Sana Tonekaboni, Lena Stempfle, Adibvafa Fallahpour +2
Foundation models trained on large-scale de-identified electronic health records (EHRs) hold promise for clinical applications. However, their capacity to memorize patient informat…
BioReason: Incentivizing Multimodal Biological Reasoning within a DNA-LLM Model
Adibvafa Fallahpour, Andrew Magnuson, Purav Gupta +8
Unlocking deep and interpretable biological reasoning from complex genomic data remains a major AI challenge limiting scientific progress. While current DNA foundation models excel…
MedSAM2: Segment Anything in 3D Medical Images and Videos
Jun Ma, Zongxin Yang, Sumin Kim +6
Medical image and video segmentation is a critical task for precision medicine, which has witnessed considerable progress in developing task or modality-specific and generalist mod…
Advancing Medical Representation Learning Through High-Quality Data
Negin Baghbanzadeh, Adibvafa Fallahpour, Yasaman Parhizkar +8
Despite the growing scale of medical Vision-Language datasets, the impact of dataset quality on model performance remains under-explored. We introduce Open-PMC, a high-quality medi…
Recent Advances, Applications and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2024 Symposium
Amin Adibi, Xu Cao, Zongliang Ji +39
The fourth Machine Learning for Health (ML4H) symposium was held in person on December 15th and 16th, 2024, in the traditional, ancestral, and unceded territories of the Musqueam,…
MedRAX: Medical Reasoning Agent for Chest X-ray
Adibvafa Fallahpour, Jun Ma, Alif Munim +2
Chest X-rays (CXRs) play an integral role in driving critical decisions in disease management and patient care. While recent innovations have led to specialized models for various…
EHRMamba: Towards Generalizable and Scalable Foundation Models for Electronic Health Records
Adibvafa Fallahpour, Mahshid Alinoori, Wenqian Ye +3
Transformers have significantly advanced the modeling of Electronic Health Records (EHR), yet their deployment in real-world healthcare is limited by several key challenges. Firstl…