Lifelonger: A benchmark for continual disease classification
MM Derakhshani, I Najdenkoska… - … Conference on Medical …, 2022 - Springer
Deep learning models have shown a great effectiveness in recognition of findings in medical
images. However, they cannot handle the ever-changing clinical environment, bringing
newly annotated medical data from different sources. To exploit the incoming streams of
data, these models would benefit largely from sequentially learning from new samples,
without forgetting the previously obtained knowledge. In this paper we introduce LifeLonger,
a benchmark for continual disease classification on the MedMNIST collection, by applying …
images. However, they cannot handle the ever-changing clinical environment, bringing
newly annotated medical data from different sources. To exploit the incoming streams of
data, these models would benefit largely from sequentially learning from new samples,
without forgetting the previously obtained knowledge. In this paper we introduce LifeLonger,
a benchmark for continual disease classification on the MedMNIST collection, by applying …
LifeLonger: A Benchmark for Continual Disease Classification
M Mahdi Derakhshani, I Najdenkoska… - arXiv e …, 2022 - ui.adsabs.harvard.edu
Deep learning models have shown a great effectiveness in recognition of findings in medical
images. However, they cannot handle the ever-changing clinical environment, bringing
newly annotated medical data from different sources. To exploit the incoming streams of
data, these models would benefit largely from sequentially learning from new samples,
without forgetting the previously obtained knowledge. In this paper we introduce LifeLonger,
a benchmark for continual disease classification on the MedMNIST collection, by applying …
images. However, they cannot handle the ever-changing clinical environment, bringing
newly annotated medical data from different sources. To exploit the incoming streams of
data, these models would benefit largely from sequentially learning from new samples,
without forgetting the previously obtained knowledge. In this paper we introduce LifeLonger,
a benchmark for continual disease classification on the MedMNIST collection, by applying …
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