Research in Artificial Intelligence and Data Science
Image processing
We use state-of-the-art deep learning and machine learning algorithms to improve image quality, solve image processing problems such as image synthesis, segmentation, and classification to support clinical needs.
Automatic Treatment Planning
We aim to utilize large-scale data sets and deep learning algorithms to enable accurate and personalized radiation dose prediction and treatment plan optimization. Our research also includes the development of data-driven decision-making tools for radiation oncologists and treatment planners. We aim to improve the effectiveness and efficiency of radiation treatment while minimizing toxicity and side effects in patients.
Outcome Prediction
We use machine learning models to predict treatment outcomes, such as tumor control and survival rates, based on patient and treatment data.
Quality Assurance
We analyze and verify treatment plan and treatment machine quality and accuracy using machine learning techniques, and to detect and prevent errors and deviations.
Natural Language Processing
We utilize large-scale datasets and advanced analytics techniques, such as deep learning and natural language processing, to extract insights and knowledge from medical records and literature, and to improve clinical decision-making and practice.
Core Faculty
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Kai Ding
Associate Professor
kai@jhu.edu
Lab: https://dinglab.jh.edu/ -
Rachel Ger
Assistant Professor
rger2@jhmi.edu -
Sarah Han-Oh
Assistant Professor
Vice Chief of Physics/Clinical-Baltimore
yhanoh1@jhmi.edu -
Tom Hrinivich
Assistant Professor
whriniv1@jhmi.edu -
Xun Jia
Professor
Chief of Medical Physics Division
xunjia@jhu.edu -
Junghoon Lee
Associate Professor
junghoon@jhu.edu
Lab: https://mica.jhu.edu/ -
Todd McNutt
Associate Professor
Director of Clinical Informatics
Director of Medical Physics Residency
tmcnutt1@jhmi.edu -
Michael Roumeliotis
Assistant Professor
Director of Brachytherapy Physics
mroumel1@jhu.edu