Abstract
The mass production of the graphics processing unit and the coronavirus disease 2019 (COVID-19) pandemic have provided the means and the motivation, respectively, for rapid developments in artificial intelligence (AI) and medical imaging techniques. This has led to new opportunities to improve patient care but also new challenges that must be overcome before these techniques are put into practice. In particular, early AI models reported high performances but failed to perform as well on new data. However, these mistakes motivated further innovation focused on developing models that were not only accurate but also stable and generalizable to new data. The recent developments in AI in response to the COVID-19 pandemic will reap future dividends by facilitating, expediting, and informing other medical AI applications and educating the broad academic audience on the topic. Furthermore, AI research on imaging animal models of infectious diseases offers a unique problem space that can fill in evidence gaps that exist in clinical infectious disease research. Here, we aim to provide a focused assessment of the AI techniques leveraged in the infectious disease imaging research space, highlight the unique challenges, and discuss burgeoning solutions.
| Original language | English (US) |
|---|---|
| Pages (from-to) | S322-S336 |
| Journal | Journal of Infectious Diseases |
| Volume | 228 |
| DOIs | |
| State | Published - Oct 1 2023 |
Funding
Financial support. This work was supported by the National Cancer Institute, National Institutes of Health (NIH; contract 75N910D00024 [task order no. 75N91019F00130, with Leidos Biomedical Research] and support to Leidos Biomedical Research through the Clinical Monitoring Research Program Directorate, Frederick National Laboratory for Cancer Research; I. C. and J. S. performed this work as employees of Leidos Biomedical Research); the National Institutes of Health Clinical Center Radiology and Imaging Sciences Center for Infectious Disease Imaging (W. T. C. and S. M. S. R.); the National Institute of Allergy and Infectious Diseases (contract HHSN272201800013C to Laulima Government Solutions; W. T. C. performed this work as an employee of Tunnell Government Services, a subcontractor of Laulima Government Solutions); the NIH Center for Interventional Oncology, the NIH Intramural Research Program, the NIH Clinical Center, the National Cancer Institute, and the National Institute of Biomedical Imaging and Bioengineering (intramural NIH grants Z1A CL040015 and 1ZIDBC011242); and the NIH Intramural Targeted Anti-COVID-19 Program, funded by the National Institute of Allergy and Infectious Diseases.
Keywords
- AI
- artificial intelligence
- imaging
- infectious disease
ASJC Scopus subject areas
- General Medicine
