24 citations · 37 across the 10 of their papers we have counts for
15 papers
All models are local: time to replace external validation with recurrent local validation
Alex Youssef, Michael Pencina, Anshul Thakur +3
External validation is often recommended to ensure the generalizability of ML models. However, it neither guarantees generalizability nor equates to a model's clinical usefulness (…
Data Encoding For Healthcare Data Democratisation and Information Leakage Prevention
Anshul Thakur, Tingting Zhu, Vinayak Abrol +3
The lack of data democratization and information leakage from trained models hinder the development and acceptance of robust deep learning-based healthcare solutions. This paper ar…
Medical records condensation: a roadmap towards healthcare data democratisation
Yujiang Wang, Anshul Thakur, Mingzhi Dong +5
The prevalence of artificial intelligence (AI) has envisioned an era of healthcare democratisation that promises every stakeholder a new and better way of life. However, the advanc…
Synthesizing Mixed-type Electronic Health Records using Diffusion Models
Taha Ceritli, Ghadeer O. Ghosheh, Vinod Kumar Chauhan +3
Electronic Health Records (EHRs) contain sensitive patient information, which presents privacy concerns when sharing such data. Synthetic data generation is a promising solution to…
Towards Scheduling Federated Deep Learning using Meta-Gradients for Inter-Hospital Learning
Rasheed el-Bouri, Tingting Zhu, David A. Clifton
Given the abundance and ease of access of personal data today, individual privacy has become of paramount importance, particularly in the healthcare domain. In this work, we aim to…
DeepMI: Deep Multi-lead ECG Fusion for Identifying Myocardial Infarction and its Occurrence-time
Girmaw Abebe Tadesse, Hamza Javed, Yong Liu +4
Myocardial Infarction (MI) has the highest mortality of all cardiovascular diseases (CVDs). Detection of MI and information regarding its occurrence-time in particular, would enabl…