Modern views of machine learning for precision psychiatry

ZS Chen, IR Galatzer-Levy, B Bigio, C Nasca, Y Zhang - Patterns, 2022 - cell.com
In light of the National Institute of Mental Health (NIMH)'s Research Domain Criteria (RDoC),
the advent of functional neuroimaging, novel technologies and methods provide new …

A review of Generative Adversarial Networks for Electronic Health Records: applications, evaluation measures and data sources

G Ghosheh, J Li, T Zhu - arXiv preprint arXiv:2203.07018, 2022 - arxiv.org
Electronic Health Records (EHRs) are a valuable asset to facilitate clinical research and
point of care applications; however, many challenges such as data privacy concerns impede …

A survey of generative adversarial networks for synthesizing structured electronic health records

GO Ghosheh, J Li, T Zhu - ACM Computing Surveys, 2024 - dl.acm.org
Electronic Health Records (EHRs) are a valuable asset to facilitate clinical research and
point of care applications; however, many challenges such as data privacy concerns impede …

ECG-Image-Kit: a synthetic image generation toolbox to facilitate deep learning-based electrocardiogram digitization

KK Shivashankara, AM Shervedani… - Physiological …, 2024 - iopscience.iop.org
Objective. Cardiovascular diseases are a major cause of mortality globally, and
electrocardiograms (ECGs) are crucial for diagnosing them. Traditionally, ECGs are stored …

[HTML][HTML] Federated learning for generating synthetic data: a scoping review

C Little, M Elliot, R Allmendinger - International Journal of …, 2023 - ncbi.nlm.nih.gov
Objectives The objective was to review current research and practices for using FL to
generate synthetic data and determine the extent to which research has been undertaken …

Multivariate generative adversarial networks and their loss functions for synthesis of multichannel ecgs

E Brophy, M De Vos, G Boylan, T Ward - Ieee Access, 2021 - ieeexplore.ieee.org
Access to medical data is highly regulated due to its sensitive nature, which can constrain
communities' ability to utilize these data for research or clinical purposes. Common de …

Generation of a Realistic Synthetic Laryngeal Cancer Cohort for AI Applications

M Katalinic, M Schenk, S Franke, A Katalinic… - Cancers, 2024 - mdpi.com
Simple Summary The use of synthetic patient data can help address patient privacy
concerns and the general availability of clinical data. It can overcome the challenges …

[HTML][HTML] Evaluation of synthetic electronic health records: A systematic review and experimental assessment

E Budu, K Etminani, A Soliman, T Rögnvaldsson - Neurocomputing, 2024 - Elsevier
Recent studies have shown how synthetic data generation methods can be applied to
electronic health records (EHRs) to obtain synthetic versions that do not violate privacy …

A Synthetic Electrocardiogram (ECG) Image Generation Toolbox to Facilitate Deep Learning-Based Scanned ECG Digitization

KK Shivashankara, R Sameni - arXiv preprint arXiv:2307.01946, 2023 - arxiv.org
Access to medical data is often limited as it contains protected health information (PHI).
There are privacy concerns regarding using records containing personally identifiable …

Optimal adjustment sets for causal query estimation in partially observed biomolecular networks

S Mohammad-Taheri, V Tewari, R Kapre… - …, 2023 - academic.oup.com
Causal query estimation in biomolecular networks commonly selects a 'valid adjustment set',
ie a subset of network variables that eliminates the bias of the estimator. A same query may …