Douglas McNair

Bill & Melinda Gates Foundation United States of America

Doug McNair serves as a Senior Advisor in Quantitative Sciences – Analytics Innovation in Global Health at the Bill & Melinda Gates Foundation. He assists the foundation’s R&D in drug and vaccine development for infectious diseases, childhood diseases, and neglected tropical diseases. Current projects include product development programs in Discovery & Translational Sciences involving Bayesian Networks. His activity also includes machine-learning and modeling of health economics collaborating with BMGF's Global Development division. Previously, Doug was President of Cerner Math Inc., responsible for Artificial Intelligence components of Cerner’s EHR solutions, discovering AI predictive models from real-world de-identified EHR-derived Big Data. Doug is lead inventor on more than 100 patents and pending patent applications, including several involving Bayesian predictive models for clinical diagnostics.

1books edited

2chapters authored

Latest work with IntechOpen by Douglas McNair

Bayesian networks (BN) have recently experienced increased interest and diverse applications in numerous areas, including economics, risk analysis and assets and liabilities management, AI and robotics, transportation systems planning and optimization, political science analytics, law and forensic science assessment of agency and culpability, pharmacology and pharmacogenomics, systems biology and metabolomics, psychology, and policy-making and social programs evaluation. This strong and varied response results not least from the fact that plausibilistic Bayesian models of structures and processes can be robust and stable representations of causal relationships. Additionally, BNs' amenability to incremental or longitudinal improvement through incorporating new data affords extra advantages compared to traditional frequentist statistical methods. Contributors to this volume elucidate various new developments in these aspects of BNs.

Go to the book

Bayesian Networks

Edited by Douglas McNair

Chapters authored

Preventing Disparities: Bayesian and Frequentist Methods for Assessing Fairness in Machine-Learning Decision-Support Models

By Douglas S. McNair

Machine-learning (ML) methods are finding increasing application to guide human decision-making in many fields. Such guidance can have important consequences, including treatments and outcomes in health care. Recently, growing attention has focused on the potential that machine-learning might automatically learn unjust or discriminatory, but unrecognized or undisclosed, patterns that are manifested in available observational data and the human processes that gave rise to them, and thereby inadvertently perpetuating and propagating injustices that are embodied in the historical data. We applied two frequentist methods that have long been utilized in the courts and elsewhere for the purpose of ascertaining fairness (Cochran-Mantel-Haenszel test and beta regression) and one Bayesian method (Bayesian Model Averaging). These methods revealed that our ML model for guiding physicians’ prescribing discharge beta-blocker medication for post-coronary artery bypass patients do not manifest significant untoward race-associated disparity. The methods also showed that our ML model for directing repeat performance of MRI imaging in children with medulloblastoma did manifest racial disparities that are likely associated with ethnic differences in informed consent and desire for information in the context of serious malignancies. The relevance of these methods to ascertaining and assuring fairness in other ML-based decision-support model-development and -curation contexts is discussed.

Part of the book: New Insights into Bayesian Inference

Introductory Chapter: Timeliness of Advantages of Bayesian Networks

By Douglas S. McNair

Part of the book: Bayesian Networks

Douglas McNair

Latest work with IntechOpen by Douglas McNair

Bayesian Networks

Chapters authored

Related collaborators

Alicia Tang

Mohammad Saber Fallah Nezhad

Marini Othman

Sunghee Oh

Ye-Mao Xia

Andino Maseleno

Shigeru Kashiwaya

Seongho Song

Niansheng Tang

Xiaoqian Zeng

Your cart