I am a computational biologist and received my PhD in Biology in 2019 from Newcastle University (United Kingdom). My PhD research focused on modeling of vegetation community distribution, developing computational methods for semi-automated vegetation classification and predicted distribution. I am currently a Postdoctoral Research Associate in the Department of Health Informatics & Data Science at Loyola University Chicago, Illinois, USA. I have been involved in numerous projects using a range of structured, unstructured and imaging data in health science and informatics. My current projects aim to utilize Artificial Intelligence (machine learning and deep learning) to understand individual-level health factors, predict outcomes and measure associated risk with different cardiac and neurological diseases.
My research interests include ensemble methods and machine/deep learning techniques to gain deeper understanding in health systems and informatics with the main aim of reliably predicting health outcomes. I am very interested in understanding clinical and public health and developing generalizable models for clinical practice and implementation, with the main aim of achieving very practical and effective outcomes. In addition, the use of electrocardiograms (ECGs) has been of primary interest to detect subtle remnants of information to predict prodromal phases of cardiac disease. My future aspiration is to also bridge deeper into mental health research, especially due to its current prevalence. Understanding and developing models in mental health-related diseases, a growing public health concern, can reduce burden of hospitals as well as reduce under-, over- or inappropriate treatment. AI in mental health has the potential to help medical providers to evolve precision medicine.
Liam Butler, PhD
Postdoctoral Research Associate
Department of Health Informatics & Data Science
Loyola University Chicago
2160 S 1st Street, CTRE 124
Maywood, IL, 60153