Kai Sun

Orcid: 0000-0002-2533-5937

Affiliations:
  • Imperial College London, UK (PhD 2014)


According to our database1, Kai Sun authored at least 16 papers between 2013 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2023
The Potential and Pitfalls of using a Large Language Model such as ChatGPT or GPT-4 as a Clinical Assistant.
CoRR, 2023

2021
A blockchain-based trust system for decentralised applications: When trustless needs trust.
Future Gener. Comput. Syst., 2021

OmiEmbed: reconstruct comprehensive phenotypic information from multi-omics data using multi-task deep learning.
CoRR, 2021

Privacy preservation in federated learning: An insightful survey from the GDPR perspective.
Comput. Secur., 2021

XOmiVAE: an interpretable deep learning model for cancer classification using high-dimensional omics data.
Briefings Bioinform., 2021

2020
GDPR-Compliant Personal Data Management: A Blockchain-Based Solution.
IEEE Trans. Inf. Forensics Secur., 2020

Privacy Preservation in Federated Learning: Insights from the GDPR Perspective.
CoRR, 2020

2019
Blockchain-based Personal Data Management: From Fiction to Solution.
Proceedings of the 18th IEEE International Symposium on Network Computing and Applications, 2019

Integrated Multi-omics Analysis Using Variational Autoencoders: Application to Pan-cancer Classification.
Proceedings of the 2019 IEEE International Conference on Bioinformatics and Biomedicine, 2019

Unsupervised Annotation of Phenotypic Abnormalities via Semantic Latent Representations on Electronic Health Records.
Proceedings of the 2019 IEEE International Conference on Bioinformatics and Biomedicine, 2019

2018
A computational framework for complex disease stratification from multiple large-scale datasets.
BMC Syst. Biol., 2018

2017
eTRIKS analytical environment: A modular high performance framework for medical data analysis.
Proceedings of the 2017 IEEE International Conference on Big Data (IEEE BigData 2017), 2017

2016
Survey on Feature Extraction and Applications of Biosignals.
Proceedings of the Machine Learning for Health Informatics, 2016

2014
Uncovering disease associations via integration of biological networks.
PhD thesis, 2014

Predicting disease associations via biological network analysis.
BMC Bioinform., 2014

2013
Graphlet-based measures are suitable for biological network comparison.
Bioinform., 2013


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