Machine learning analysis methods offer the opportunity to integrate and learn from large amounts of biological, clinical, and environmental data, and there is a growing interest in how these tools can be used to inform and individualize clinical decision making in a variety of disease areas. Machine learning can offer different, yet often complementary, insights compared to traditional statistical analyses to better understand heterogeneity in patient presentation, prognoses, and treatment response, generating critical data for precision medicine research. These methods can allow integration across diverse data types and large feature sets, overcoming some limitations of traditional tools to answer clinical questions. However, many clinical researchers have little exposure to machine learning methods, presenting a barrier to utilization of these tools themselves and/or to effective collaboration with methodologists in their own research.
The objectives of this series are to:
- Provide a background/foundation of knowledge regarding the use of machine learning tools in clinical questions
- Understand the strengths and limitations of these methods
- Recognize some real-world examples of applied machine learning methodology in clinical research
- Elucidate how machine learning can be used to advance precision medicine research
On May 11, 2022, clinicians and researchers will discuss examples of how machine learning tools have been applied in arthritis and autoimmune disease. This session will feature an overview of machine learning and its application to identify clinical phenotypes of osteoarthritis and type 1 diabetes.
| May 11, 2022 agenda Machine Learning Tools & Precision Medicine in Arthritis & Autoimmunity |
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| 9:30am | Machine learning didactic overview (unsupervised vs supervised methods, advantages, limitations, requisite data requirements) (Daniel de Marchi) | |
| 10:00am | Type 1 Diabetes phenotypes (Anna Kahkoska) | |
| 10:30am | Osteoarthritis phenotypes (Amanda Nelson and Tom Keefe) | |
| 11:00am | Q&A/panel questions and discussion | |
| 11:30am |
Event ends |
Click here to watch the recording from the May 11 event.
On May 18, 2022, clinicians and researchers will explore the use of machine learning tools and precision medicine techniques in clinical research. This session will feature an overview of machine learning tools in the field of precision medicine and address how they may be used to inform decision support for peripheral artery disease and rare genetic diseases.
| May 18, 2022 agenda Machine Learning Tools & Precision Medicine in Clinical Research |
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| 1:00pm | Precision medicine overview and SMART trial designs and how those can be used with ML methods to infer precision medicine decision support (John Sperger) | |
| 1:30pm | Precision medicine machine learning analytics to improve PAD treatment decisions and outcomes (Katharine McGinigle and Nikki Freeman) | |
| 2:00pm | Machine learning with EHR data: Addressing diagnostic odysseys among pediatric patients with rare genetic diseases (Michael Adams and Kushal Shah) | |
| 2:30pm | Q&A/panel questions and discussion | |
| 3:00pm |
Event ends |
Click here to watch the recording from the May 18 event.
Integrating Machine Learning into Clinical Research & Health Care
On May 25, 2022 from 1:00-3:00pm, clinicians and researchers will share ideas about early-stage machine learning projects, and a panel discussion will focus on how researchers and clinicians at UNC can integrate machine learning techniques into their own clinical research. Are you a clinician with an idea for how patient care could be improved with computational decision support tools? Pitch your idea (5-10 minute overview) to assembled machine learning experts on May 25. Receive expert guidance and compete for funding from the UNC Program for Precision Medicine in Health Care for analytical support to develop your project. Emailprecisionmedicine@med.unc.edufor more information about the pitch opportunity.
| May 25, 2022 agenda Integrating Machine Learning into Clinical Research & Health Care |
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| 1:00pm | Opening remarks | |
| 1:10pm | Pitches (4 @ 15 minutes each) | |
| 2:10pm | Overview of Data Science Lab at NC TraCS (Peter Leese) | |
| 2:25pm | Q&A and discussion | |
| 3:00pm | Event ends |
Click here to watch the recording from the May 25 event.
We encourage anyone interested in using machine learning as part of their own research to attend, regardless of research background or experience with machine learning!
The goal of this seminar series is to bring together researchers and clinicians across the UNC campus and catalyze new clinical research using machine learning. All backgrounds and experience levels will find this series engaging and informative.
This series is jointly sponsored by the UNC Core Center for Clinical Research (CCCR) and the UNC Program for Precision Medicine in Health Care (PPMH). All events will be virtual (Zoom) and free of charge.
Register separately for each event in the series.
Click here to register for May 11, 2022, 9:30-11:30am.
Click here to register for May 18, 2022, 1:00-3:00pm.
Click here to register for May 25, 2022, 1:00-3:00pm.
Email precisionmedicine@med.unc.edu for more information.
Click here to download the event flyer: flyer Machine Learning series May2022
