{"id":15896,"date":"2025-11-11T11:44:13","date_gmt":"2025-11-11T16:44:13","guid":{"rendered":"https:\/\/med.virginia.edu\/radiology\/?p=15896"},"modified":"2025-11-17T08:40:50","modified_gmt":"2025-11-17T13:40:50","slug":"uva-radiology-grand-rounds-prediction-inference-and-overparameterization-in-machine-learning-with-jeffrey-d-blume-phd","status":"publish","type":"post","link":"https:\/\/med.virginia.edu\/radiology\/2025\/11\/11\/uva-radiology-grand-rounds-prediction-inference-and-overparameterization-in-machine-learning-with-jeffrey-d-blume-phd\/","title":{"rendered":"UVA Radiology Grand Rounds \u2014 &#8220;Prediction, Inference and Overparameterization in Machine Learning&#8221; with Jeffrey D. Blume, PhD"},"content":{"rendered":"<div class=\"video-wrapper\"><iframe loading=\"lazy\" title=\"UVA Radiology Grand Rounds: \u201cPrediction, Inference, &amp; More in Machine Learning\u201d with Jeffrey Blume\" width=\"500\" height=\"281\" src=\"https:\/\/www.youtube.com\/embed\/kHuV2YpBX7E?feature=oembed\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" allowfullscreen><\/iframe><\/div>\n<p style=\"text-align: center\"><b>Prediction, Inference and Overparameterization in Machine Learning: Guiding Intuition for Clinical AI<br \/>\n<\/b>Jeffrey D. Blume, PhD<br \/>\nNovember 12, 2025<\/p>\n<p><em>Machine learning models are the engines of AI and are increasingly applied in clinical practice, yet their goals and behavior often differ from traditional statistical models. This talk will develop intuition for how prediction, inference, and overparameterization interact; using simple examples to reveal when complex models help, and when they can mislead. We\u2019ll discuss practical ways to evaluate and trust model outputs in clinical settings where interpretability and generalization matter most.<\/em><\/p>\n<p><em>Learning objectives:<\/em><\/p>\n<ol>\n<li><em>Differentiate prediction from inference<\/em><\/li>\n<li><em>Recognize the implications of overparameterization in modern machine learning<\/em><\/li>\n<li><em>Integrate statistical reasoning into clinical evaluation of AI<\/em><\/li>\n<\/ol>\n<p>To view previous Grand Rounds lectures, <a href=\"https:\/\/med.virginia.edu\/radiology\/about-us\/career-professional-development\/#grandrounds\">click here<\/a>.<\/p>\n<hr \/>\n<h3>About the Lecturer \u2014 Jeffrey D. Blume, PhD<\/h3>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-15897 size-full alignleft\" src=\"https:\/\/med.virginia.edu\/radiology\/wp-content\/uploads\/sites\/191\/2025\/11\/jeffrey_blume_6086.jpeg\" alt=\"\" width=\"300\" height=\"300\" srcset=\"https:\/\/med.virginia.edu\/radiology\/wp-content\/uploads\/sites\/191\/2025\/11\/jeffrey_blume_6086.jpeg 300w, https:\/\/med.virginia.edu\/radiology\/wp-content\/uploads\/sites\/191\/2025\/11\/jeffrey_blume_6086-150x150.jpeg 150w, https:\/\/med.virginia.edu\/radiology\/wp-content\/uploads\/sites\/191\/2025\/11\/jeffrey_blume_6086-200x200.jpeg 200w, https:\/\/med.virginia.edu\/radiology\/wp-content\/uploads\/sites\/191\/2025\/11\/jeffrey_blume_6086-100x100.jpeg 100w, https:\/\/med.virginia.edu\/radiology\/wp-content\/uploads\/sites\/191\/2025\/11\/jeffrey_blume_6086-70x70.jpeg 70w\" sizes=\"(max-width: 300px) 100vw, 300px\" \/><\/p>\n<p>Dr. Jeffrey D. Blume is Professor of Data Science and Quantitative Foundation Associate Dean for Academics and Faculty Affairs at the University of Virginia School of Data Science. A biostatistician by training, he is a leading expert in likelihood\u2010based methods for measuring statistical evidence and the inventor of the second-generation p-value, a framework for improving statistical inference and reproducibility in data-rich settings. His research spans prediction modeling \u00ad\u00ad\u2013 including methods for handling missing data, high-dimensional model selection and post-selection inference \u2013 mediation modeling, ROC analysis, and clinical trial design, particularly in diagnostic and imaging studies. Dr. Blume has served as lead statistician on numerous large-scale multisite trials and currently co-leads an NCI-funded project examining disparities in lung-cancer screening, for which he and his collaborators received Vanderbilt\u2019s Chancellor\u2019s Award for Research. He also served for more than a decade on the faculty of the Radiological Society of North America\u2019s (RSNA\u2019s) Clinical Trials Methodology Workshop (CTMW), including five years as its co-leader. His collaborative experience spans radiology, nephrology, women\u2019s health, and neuroscience, including service on multiple data safety monitoring boards. As Director of the PRISM Lab (\u201cPrediction, Inference, and Scale in Data Science Models\u201d), Dr. Blume mentors PhD students developing novel tools to bridge methodological innovation with applied biomedical research. A Fellow of the American Statistical Association and the American Association for the Advancement of Science, he was also awarded the Spinoza Chair in Medicine by the University of Amsterdam in 2019.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Prediction, Inference and Overparameterization in Machine Learning: Guiding Intuition for Clinical AI Jeffrey D. Blume, PhD November 12, 2025 Machine learning models are the engines of AI and are increasingly applied in clinical practice, yet their goals and behavior often differ from traditional statistical models. This talk will develop intuition for how prediction, inference, and [&hellip;]<\/p>\n","protected":false},"author":1969,"featured_media":15897,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":"","_links_to":"","_links_to_target":""},"categories":[57,1],"tags":[],"class_list":["post-15896","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-events","category-news"],"acf":false,"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.1.1 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>UVA Radiology Grand Rounds \u2014 &quot;Prediction, Inference and Overparameterization in Machine Learning&quot; with Jeffrey D. Blume, PhD - Radiology and Medical Imaging<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/med.virginia.edu\/radiology\/2025\/11\/11\/uva-radiology-grand-rounds-prediction-inference-and-overparameterization-in-machine-learning-with-jeffrey-d-blume-phd\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"UVA Radiology Grand Rounds \u2014 &quot;Prediction, Inference and Overparameterization in Machine Learning&quot; with Jeffrey D. Blume, PhD - Radiology and Medical Imaging\" \/>\n<meta property=\"og:description\" content=\"Prediction, Inference and Overparameterization in Machine Learning: Guiding Intuition for Clinical AI Jeffrey D. Blume, PhD November 12, 2025 Machine learning models are the engines of AI and are increasingly applied in clinical practice, yet their goals and behavior often differ from traditional statistical models. This talk will develop intuition for how prediction, inference, and [&hellip;]\" \/>\n<meta property=\"og:url\" content=\"https:\/\/med.virginia.edu\/radiology\/2025\/11\/11\/uva-radiology-grand-rounds-prediction-inference-and-overparameterization-in-machine-learning-with-jeffrey-d-blume-phd\/\" \/>\n<meta property=\"og:site_name\" content=\"Radiology and Medical Imaging\" \/>\n<meta property=\"article:published_time\" content=\"2025-11-11T16:44:13+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2025-11-17T13:40:50+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/med.virginia.edu\/radiology\/wp-content\/uploads\/sites\/191\/2025\/11\/jeffrey_blume_6086.jpeg\" \/>\n\t<meta property=\"og:image:width\" content=\"300\" \/>\n\t<meta property=\"og:image:height\" content=\"300\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"Henry Lin-David\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Henry Lin-David\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"3 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/med.virginia.edu\/radiology\/2025\/11\/11\/uva-radiology-grand-rounds-prediction-inference-and-overparameterization-in-machine-learning-with-jeffrey-d-blume-phd\/\",\"url\":\"https:\/\/med.virginia.edu\/radiology\/2025\/11\/11\/uva-radiology-grand-rounds-prediction-inference-and-overparameterization-in-machine-learning-with-jeffrey-d-blume-phd\/\",\"name\":\"UVA Radiology Grand Rounds \u2014 \\\"Prediction, Inference and Overparameterization in Machine Learning\\\" with Jeffrey D. 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