73 citations · 73 across the 5 of their papers we have counts for
6 papers
Confident but Unreliable: A Behavioral Safety Audit of Vision-Language Models on Brain MRI
Amir Sabbaghziarani, Mohammadsajad Abavisani, Sergey Plis
Vision-language models (VLMs), including medical specialists, are increasingly proposed for medical imaging, yet their stated confidence is rarely evaluated separately from correct…
Causal Graph Recovery in Neuroimaging through Answer Set Programming
Mohammadsajad Abavisani, Kseniya Solovyeva, David Danks +2
Learning graphical causal structures from time series data presents significant challenges, especially when the measurement frequency does not match the causal timescale of the sys…
ION-C: Integration of Overlapping Networks via Constraints
Praveen Nair, Payal Bhandari, Mohammadsajad Abavisani +2
In many causal learning problems, variables of interest are often not all measured over the same observations, but are instead distributed across multiple datasets with overlapping…
GRACE-C: Generalized Rate Agnostic Causal Estimation via Constraints
Mohammadsajad Abavisani, David Danks, Sergey Plis
Graphical structures estimated by causal learning algorithms from time series data can provide misleading causal information if the causal timescale of the generating process fails…
Radiologist-Level COVID-19 Detection Using CT Scans with Detail-Oriented Capsule Networks
Aryan Mobiny, Pietro Antonio Cicalese, Samira Zare +6
Radiographic images offer an alternative method for the rapid screening and monitoring of Coronavirus Disease 2019 (COVID-19) patients. This approach is limited by the shortage of…
Greedy AutoAugment
Alireza Naghizadeh, Mohammadsajad Abavisani, Dimitris N. Metaxas
A major problem in data augmentation is to ensure that the generated new samples cover the search space. This is a challenging problem and requires exploration for data augmentatio…