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.

Bibliographische Detailangaben
Hauptverfasser: Alam, Salman, Oni, Atquiya Labiba, Samir, Jubair, Hossain, Asif Mosharrof
Weitere Verfasser: Alam, Md.Golam Rabiul
Format: Abschlussarbeit
Sprache:English
Veröffentlicht: Brac University 2023
Schlagworte:
Sickle cell
Clinical data
Genotype
Federated learning
Few-shot siamese
Federated siamese bidirectional LSTM
Machine learning
Computer algorithms
Sickle cell anemia
Online Zugang:http://hdl.handle.net/10361/21953
Beschreibung
Zusammenfassung:This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2023.

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