Jun 23, 2026 · 29 min · 17 segments
In this episode, we talk with Dr. Ji Soo Kim about a new tool designed to help people with scleroderma better understand and manage their disease. Using information collected over many years from…
Ji Soo KimGuestVicky ShamagamHostManaging scleroderma can feel like trying to make sense of innumerable disconnected data points.
Well, with the power of statistics and high throughput computing, perhaps that is all about to change.
The manuscript we will discuss today is Development of a Personalized Visualization and Analysis Tool to Improve Clinical Care in Complex Multisystem Diseases with Application to Scleroderma.
It was published in Arthritis Care and Research, and a link to the manuscript and disclosures is available in today's show notes.
I'm delighted to be joined by the first author of this manuscript, Dr. Ji Soo Kim.
Dr. Kim is an assistant professor at the Johns Hopkins School of Medicine with a joint appointment in biostatistics at the Johns Hopkins School of Public Health.
Her research focuses on developing statistical methodology, including efficient estimation of patient trajectories in high-dimensional settings to effectively model personalized interventions.
To translate these methods into clinical settings, Dr. Kim has developed an interactive data visualization tool to illustrate patient's disease state and clinical trajectory and to define individualized risk predictions for major complications.
Her recent work includes studying the complex relationships of the immune response in cancer and identifying latent subgroups of patients who share similar multivariate pulmonary function trajectories.
The work Dr. Kim will discuss today focuses on scleroderma, but she's also extending this analytic framework to other rheumatic diseases, including psoriatic arthritis, myositis, vasculitis, and Sjogren's disease, in which biomarker trajectories also play a critical role in clinical decision-making.
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Managing scleroderma can feel like trying to make sense of innumerable disconnected data points.
Well, with the power of statistics and high throughput computing, perhaps that is all about to change.
The manuscript we will discuss today is Development of a Personalized Visualization and Analysis Tool to Improve Clinical Care in Complex Multisystem Diseases with Application to Scleroderma.
It was published in Arthritis Care and Research, and a link to the manuscript and disclosures is available in today's show notes.
I'm delighted to be joined by the first author of this manuscript, Dr. Ji Soo Kim.
Dr. Kim is an assistant professor at the Johns Hopkins School of Medicine with a joint appointment in biostatistics at the Johns Hopkins School of Public Health.
Her research focuses on developing statistical methodology, including efficient estimation of patient trajectories in high-dimensional settings to effectively model personalized interventions.
To translate these methods into clinical settings, Dr. Kim has developed an interactive data visualization tool to illustrate patient's disease state and clinical trajectory and to define individualized risk predictions for major complications.
Her recent work includes studying the complex relationships of the immune response in cancer and identifying latent subgroups of patients who share similar multivariate pulmonary function trajectories.
The work Dr. Kim will discuss today focuses on scleroderma, but she's also extending this analytic framework to other rheumatic diseases, including psoriatic arthritis, myositis, vasculitis, and Sjogren's disease, in which biomarker trajectories also play a critical role in clinical decision-making.
