Usage Information
Abstract
In the 18th century, Thomas Bayes developed his eponymous theorem that teaches us that pretest probabilities can be altered by new information, such as when game show host Monty Hall revealed the goat behind one of the remaining doors in “Let’s Make A Deal.” Bayesian analysis is a key feature of many medical decisions. In this issue of the JCI, Lee and colleagues apply this concept to inflammatory bowel disease to identify gene expression–based biomarkers of disease severity. Importantly, these biomarkers allowed patients to be stratified into two groups: those at high risk for disease recurrence or the need for immunosuppressive treatment escalation and those with a more benign disease course.
Authors
David J. Friedman, Laurence A. Turka, Simon C. Robson
Usage data is cumulative from May 2025 through May 2026.
| Usage | JCI | PMC |
|---|---|---|
| Text version | 380 | 64 |
| 171 | 10 | |
| Figure | 289 | 2 |
| Citation downloads | 141 | 0 |
| Totals | 981 | 76 |
| Total Views | 1,057 | |
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.
Copyright © 2026 American Society for Clinical Investigation
ISSN: 0021-9738 (print), 1558-8238 (online)