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.

Библиографические подробности
Главные авторы: Alam, Salman, Oni, Atquiya Labiba, Samir, Jubair, Hossain, Asif Mosharrof
Другие авторы: Alam, Md.Golam Rabiul
Формат: Диссертация
Язык:English
Опубликовано: Brac University 2023
Предметы:
Sickle cell
Clinical data
Genotype
Federated learning
Few-shot siamese
Federated siamese bidirectional LSTM
Machine learning
Computer algorithms
Sickle cell anemia
Online-ссылка:http://hdl.handle.net/10361/21953

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