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GitHub / fitushar / multi-label-weakly-supervised-classification-of-body-ct

A rule-based algorithm enabled the automatic extraction of disease labels from tens of thousands of radiology reports. These weak labels were used to create deep learning models to classify multiple diseases for three different organ systems in body CT.

JSON API: http://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/fitushar%2Fmulti-label-weakly-supervised-classification-of-body-ct

Stars: 8
Forks: 1
Open issues: 0

License: None
Language: Python
Size: 1.78 MB
Dependencies parsed at: Pending

Created at: almost 4 years ago
Updated at: 14 days ago
Pushed at: 14 days ago
Last synced at: 14 days ago

Topics: 3d, 3d-classification, 3d-resnet, 3d-segmentation, ct, ct-scan-images, kidney, kidney-disease, kidney-disease-prediction, liver-disease, liver-disease-prediction, machine-learning, multi-label-disease, multi-label-disease-classification, multi-label-image-classification, rule-based-modeling, tensorflow2, weakly-supervised-learning

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