Blockchain meets federated learning in healthcare: A systematic review with challenges and opportunities
R Myrzashova, SH Alsamhi… - IEEE Internet of …, 2023 - ieeexplore.ieee.org
Recently, innovations in the Internet of Medical Things (IoMT), information and
communication technologies, and machine learning (ML) have enabled smart healthcare …
communication technologies, and machine learning (ML) have enabled smart healthcare …
Risk factors associated with coronary heart disease in women: a systematic review
MF Bai, X Wang - Herz, 2020 - Springer
In the context of global aging, cardiovascular disease has become the number one cause of
death among Chinese women. Lifestyle factors play an important role in the development of …
death among Chinese women. Lifestyle factors play an important role in the development of …
A blockchain-empowered federated learning in healthcare-based cyber physical systems
With the rapid development of healthcare-based cyber physical systems (CPSs), more and
more healthcare data is collected from clinical institutions or hospitals. Due to the private …
more healthcare data is collected from clinical institutions or hospitals. Due to the private …
Learning from electronic health records across multiple sites: A communication-efficient and privacy-preserving distributed algorithm
Objectives We propose a one-shot, privacy-preserving distributed algorithm to perform
logistic regression (ODAL) across multiple clinical sites. Materials and Methods ODAL …
logistic regression (ODAL) across multiple clinical sites. Materials and Methods ODAL …
Learning from local to global: An efficient distributed algorithm for modeling time-to-event data
Objective We developed and evaluated a privacy-preserving One-shot Distributed Algorithm
to fit a multicenter Cox proportional hazards model (ODAC) without sharing patient-level …
to fit a multicenter Cox proportional hazards model (ODAC) without sharing patient-level …
Distributed learning for heterogeneous clinical data with application to integrating COVID-19 data across 230 sites
Integrating real-world data (RWD) from several clinical sites offers great opportunities to
improve estimation with a more general population compared to analyses based on a single …
improve estimation with a more general population compared to analyses based on a single …
ODAL: A one-shot distributed algorithm to perform logistic regressions on electronic health records data from multiple clinical sites
Electronic Health Records (EHR) contain extensive information on various health outcomes
and risk factors, and therefore have been broadly used in healthcare research. Integrating …
and risk factors, and therefore have been broadly used in healthcare research. Integrating …
Phe2vec: Automated disease phenotyping based on unsupervised embeddings from electronic health records
Robust phenotyping of patients from electronic health records (EHRs) at scale is a challenge
in clinical informatics. Here, we introduce Phe2vec, an automated framework for disease …
in clinical informatics. Here, we introduce Phe2vec, an automated framework for disease …
ODACH: a one-shot distributed algorithm for Cox model with heterogeneous multi-center data
We developed a One-shot Distributed Algorithm for Cox proportional-hazards model to
analyze Heterogeneous multi-center time-to-event data (ODACH) circumventing the need …
analyze Heterogeneous multi-center time-to-event data (ODACH) circumventing the need …
Month of birth and mental disorders: A population‐based study and validation using global meta‐analysis
Objective Month of birth (MOB) is associated with specified mental disorders (MDs).
However, whether these relationships extend to all MDs remains unclear. We investigate the …
However, whether these relationships extend to all MDs remains unclear. We investigate the …