DeepMalaria successfully performs virtual screening for Plasmodium falciparum. State-of-the-art deep learning techniques such as transfer learning and hyper-parameter optimization through external validation are leveraged to create a practical and accurate pipeline in silico.
Through deep learning the patterns within the Electrocardiogram signals are learnt and utilized to classify arrhythmia within the patients. This work uses the patterns learnt from the 2D domain (images) to featurize the ECG signals. Results showed an scale-able model which is more accurate than human cardiologists.
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