6 citations · 6 across the 3 of their papers we have counts for
3 papers
Democratising Clinical AI through Dataset Condensation for Classical Clinical Models
Anshul Thakur, Soheila Molaei, Pafue Christy Nganjimi +5
Dataset condensation (DC) learns a compact synthetic dataset that enables models to match the performance of full-data training, prioritising utility over distributional fidelity.…
Deep Reinforcement Learning for Multi-class Imbalanced Training
Jenny Yang, Rasheed El-Bouri, Odhran O'Donoghue +3
With the rapid growth of memory and computing power, datasets are becoming increasingly complex and imbalanced. This is especially severe in the context of clinical data, where the…
Privacy-aware Early Detection of COVID-19 through Adversarial Training
Omid Rohanian, Samaneh Kouchaki, Andrew Soltan +4
Early detection of COVID-19 is an ongoing area of research that can help with triage, monitoring and general health assessment of potential patients and may reduce operational stra…