Prediction of genetic mutation from clinical data of sickle cell disease using few-shot siamese bidirectional LSTM and federated learning

Prediction of genetic mutation from clinical data of sickle cell disease using few-shot siamese bidirectional LSTM and federated learning

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2023.

Podrobná bibliografie
Hlavní autoři: Alam, Salman, Oni, Atquiya Labiba, Samir, Jubair, Hossain, Asif Mosharrof
Další autoři: Alam, Md.Golam Rabiul
Médium: Diplomová práce
Jazyk:English
Vydáno: Brac University 2023
Témata:
Sickle cell
Clinical data
Genotype
Federated learning
Few-shot siamese
Federated siamese bidirectional LSTM
Machine learning
Computer algorithms
Sickle cell anemia
On-line přístup:http://hdl.handle.net/10361/21953

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