Human-Centered Design to Address Biases in Artificial Intelligence
You Chen, Ellen Wright Clayton, Laurie Lovett Novak, Shilo Anders, Bradley Malin
The potential of artificial intelligence (AI) to reduce health care disparities and inequities is recognized, but it can also exacerbate these issues if not implemented in an equitable manner…
Victor A Borza, Ellen Wright Clayton, Murat Kantarcioglu, Yevgeniy Vorobeychik, Bradley Malin
Scientific and clinical studies have a long history of bias in recruitment of underprivileged and minority populations. This underrepresentation leads to inaccurate, inapplicable, and non-generalizable results…
Enhancing Fairness in Disease Prediction with Optimizing Multiple Domain Adversarial Networks
Bin Li, Xinghua Shi, Hongchang Gao, Xiaoqian Jiang, Kai Zhang, Arif O Harmanci, Bradley Malin
Predictive models in biomedicine need to ensure equitable and reliable outcomes for the populations they are applied to. Unfortunately, biases in medical predictions can lead to unfair treatment and widening disparities…
Split Learning for Distributed Collaborative Training of Deep Learning Models in Health Informatics
Li Z, Yan C, Zhang X, Gharibi G, Yin Z, Jiang X, Malin BA
Deep learning continues to rapidly evolve and is now demonstrating remarkable potential for numerous medical prediction tasks. However, realizing deep learning models that generalize across healthcare organizations is challenging…
Towards Fair Patient-Trial Matching via Patient-Criterion Level Fairness Constraint
Chang C-Y, Yuan J, Ding S, Tan Q, Zhang K, Jiang X, Hu X, Zou N
Clinical trials are indispensable in developing new treatments, but they face obstacles in patient recruitment and retention, hindering the enrollment of necessary participants. To tackle these challenges, deep learning frameworks have been created to match patients to trials…
Sensitive Data Detection with High-Throughput Machine Learning Models in Electrical Health Records
Zhang K, Jiang X
In the era of big data, there is an increasing need for healthcare providers, communities, and researchers to share data and collaborate to improve health outcomes, generate valuable insights, and advance research. The Health Insurance Portability and Accountability Act of 1996 (HIPAA) is a federal law designed to protect sensitive health information by defining regulations for protected health information (PHI). However, it does not provide efficient tools for detecting or removing PHI before data sharing…
Does Synthetic Data Generation of LLMs Help Clinical Text Mining?
Tang R, Han X, Jiang X, Hu X
Recent advancements in large language models (LLMs) have led to the development of highly potent models like OpenAI’s ChatGPT. These models have exhibited exceptional performance in a variety of tasks, such as question answering, essay composition, and code generation. However, their effectiveness in the healthcare sector remains uncertain…