48 citations · 62 across the 10 of their papers we have counts for
10 papers
An Empirical Analysis of Continual Learning for Heterogeneous Medical Visual Question Answering
Mai A. Shaaban, Tausifa Jan Saleem, Alaa Mohamed +3
Deploying medical visual question answering (MedVQA) systems in real-world clinical settings requires models that adapt to new clinical tasks without forgetting previously acquired…
AURORA: Adaptive Unified Representation for Robust Ultrasound Analysis
Ufaq Khan, L. D. M. S. Sai Teja, Ayuba Shakiru +4
Ultrasound images vary widely across scanners, operators, and anatomical targets, which often causes models trained in one setting to generalize poorly to new hospitals and clinica…
MOTOR: Multimodal Optimal Transport via Grounded Retrieval in Medical Visual Question Answering
Mai A. Shaaban, Tausifa Jan Saleem, Vijay Ram Papineni +1
Medical visual question answering (MedVQA) plays a vital role in clinical decision-making by providing contextually rich answers to image-based queries. Although vision-language mo…
TactileNet: Bridging the Accessibility Gap with AI-Generated Tactile Graphics for Individuals with Vision Impairment
Adnan Khan, Alireza Choubineh, Mai A. Shaaban +2
Tactile graphics are essential for providing access to visual information for the 43 million people globally living with vision loss. Traditional methods for creating these graphic…
MedPromptX: Grounded Multimodal Prompting for Chest X-ray Diagnosis
Mai A. Shaaban, Adnan Khan, Mohammad Yaqub
Chest X-ray images are commonly used for predicting acute and chronic cardiopulmonary conditions, but efforts to integrate them with structured clinical data face challenges due to…
Fine-Tuned Large Language Models for Symptom Recognition from Spanish Clinical Text
Mai A. Shaaban, Abbas Akkasi, Adnan Khan +2
The accurate recognition of symptoms in clinical reports is significantly important in the fields of healthcare and biomedical natural language processing. These entities serve as…
Improving Pseudo-labelling and Enhancing Robustness for Semi-Supervised Domain Generalization
Adnan Khan, Mai A. Shaaban, Muhammad Haris Khan
Beyond attaining domain generalization (DG), visual recognition models should also be data-efficient during learning by leveraging limited labels. We study the problem of Semi-Supe…
PECon: Contrastive Pretraining to Enhance Feature Alignment between CT and EHR Data for Improved Pulmonary Embolism Diagnosis
Santosh Sanjeev, Salwa K. Al Khatib, Mai A. Shaaban +3
Previous deep learning efforts have focused on improving the performance of Pulmonary Embolism(PE) diagnosis from Computed Tomography (CT) scans using Convolutional Neural Networks…
OptBA: Optimizing Hyperparameters with the Bees Algorithm for Improved Medical Text Classification
Mai A. Shaaban, Mariam Kashkash, Maryam Alghfeli +1
One of the main challenges in the field of deep learning is obtaining the optimal model hyperparameters. The search for optimal hyperparameters usually hinders the progress of solu…
Deep convolutional forest: a dynamic deep ensemble approach for spam detection in text
Mai A. Shaaban, Yasser F. Hassan, Shawkat K. Guirguis
The increase in people's use of mobile messaging services has led to the spread of social engineering attacks like phishing, considering that spam text is one of the main factors i…