30 citations · 63 across the 8 of their papers we have counts for
8 papers
When AI Democratizes Exploitation: LLM-Assisted Strategic Manipulation of Fair Division Algorithms
Priyanka Verma, Balagopal Unnikrishnan
Fair resource division algorithms, like those implemented in Spliddit platform, have traditionally been considered difficult for the end users to manipulate due to its complexities…
Beyond Ethics: How Inclusive Innovation Drives Economic Returns in Medical AI
Balagopal Unnikrishnan, Ariel Guerra Adames, Amin Adibi +10
While ethical arguments for fairness in healthcare AI are well-established, the economic and strategic value of inclusive design remains underexplored. This perspective introduces…
Red Teaming Large Language Models for Healthcare
Vahid Balazadeh, Michael Cooper, David Pellow +32
We present the design process and findings of the pre-conference workshop at the Machine Learning for Healthcare Conference (2024) entitled Red Teaming Large Language Models for He…
Semi-supervised classification of radiology images with NoTeacher: A Teacher that is not Mean
Balagopal Unnikrishnan, Cuong Nguyen, Shafa Balaram +3
Deep learning models achieve strong performance for radiology image classification, but their practical application is bottlenecked by the need for large labeled training datasets.…
Self-Path: Self-supervision for Classification of Pathology Images with Limited Annotations
Navid Alemi Koohbanani, Balagopal Unnikrishnan, Syed Ali Khurram +2
While high-resolution pathology images lend themselves well to `data hungry' deep learning algorithms, obtaining exhaustive annotations on these images is a major challenge. In thi…
Semi-supervised and Unsupervised Methods for Heart Sounds Classification in Restricted Data Environments
Balagopal Unnikrishnan, Pranshu Ranjan Singh, Xulei Yang +1
Automated heart sounds classification is a much-required diagnostic tool in the view of increasing incidences of heart related diseases worldwide. In this study, we conduct a compr…
CaRENets: Compact and Resource-Efficient CNN for Homomorphic Inference on Encrypted Medical Images
Jin Chao, Ahmad Al Badawi, Balagopal Unnikrishnan +9
Convolutional neural networks (CNNs) have enabled significant performance leaps in medical image classification tasks. However, translating neural network models for clinical appli…
Semi-Supervised Deep Learning for Abnormality Classification in Retinal Images
Bruno Lecouat, Ken Chang, Chuan-Sheng Foo +7
Supervised deep learning algorithms have enabled significant performance gains in medical image classification tasks. But these methods rely on large labeled datasets that require…