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.

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριοι συγγραφείς: Alam, Salman, Oni, Atquiya Labiba, Samir, Jubair, Hossain, Asif Mosharrof
Άλλοι συγγραφείς: Alam, Md.Golam Rabiul
Μορφή: Thesis
Γλώσσα:English
Έκδοση: Brac University 2023
Θέματα:
Sickle cell
Clinical data
Genotype
Federated learning
Few-shot siamese
Federated siamese bidirectional LSTM
Machine learning
Computer algorithms
Sickle cell anemia
Διαθέσιμο Online:http://hdl.handle.net/10361/21953

Διαδίκτυο

http://hdl.handle.net/10361/21953

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