Emerging use of artificial intelligence in inflammatory bowel disease
| Autor: | Alexander N. Levy, Arushi Kohli, Erik A. Holzwanger |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Artificial intelligence
Treatment response Colorectal neoplasia screening Inflammatory bowel disease Predictive models Machine Learning 03 medical and health sciences 0302 clinical medicine Humans Medicine Multiomic data Automated diagnostics business.industry Genomic sequencing Gastroenterology Minireviews General Medicine Colitis Inflammatory Bowel Diseases medicine.disease digestive system diseases Gastrointestinal disorder Analytics 030220 oncology & carcinogenesis 030211 gastroenterology & hepatology business |
| Zdroj: | World Journal of Gastroenterology |
| ISSN: | 1007-9327 |
| Popis: | Inflammatory bowel disease (IBD) is a complex, immune-mediated gastrointestinal disorder with ill-defined etiology, multifaceted diagnostic criteria, and unpredictable treatment response. Innovations in IBD diagnostics, including developments in genomic sequencing and molecular analytics, have generated tremendous interest in leveraging these large data platforms into clinically meaningful tools. Artificial intelligence, through machine learning facilitates the interpretation of large arrays of data, and may provide insight to improving IBD outcomes. While potential applications of machine learning models are vast, further research is needed to generate standardized models that can be adapted to target IBD populations. |
| Databáze: | OpenAIRE |
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