Machine and deep learning in inflammatory bowel disease

التفاصيل البيبلوغرافية
العنوان:	Machine and deep learning in inflammatory bowel disease
المؤلفون:	Zulqarnain, Fatima, Rhoads, S. Fisher, Syed, Sana
المصدر:	Current Opinion in Gastroenterology ; ISSN 0267-1379 1531-7056
بيانات النشر:	Ovid Technologies (Wolters Kluwer Health)
سنة النشر:	2023
الوصف:	Purpose of review The Management of inflammatory bowel disease (IBD) has evolved with the introduction and widespread adoption of biologic agents; however, the advent of artificial intelligence technologies like machine learning and deep learning presents another watershed moment in IBD treatment. Interest in these methods in IBD research has increased over the past 10 years, and they offer a promising path to better clinical outcomes for IBD patients. Recent findings Developing new tools to evaluate IBD and inform clinical management is challenging because of the expansive volume of data and requisite manual interpretation of data. Recently, machine and deep learning models have been used to streamline diagnosis and evaluation of IBD by automating review of data from several diagnostic modalities with high accuracy. These methods decrease the amount of time that clinicians spend manually reviewing data to formulate an assessment. Summary Interest in machine and deep learning is increasing in medicine, and these methods are poised to revolutionize the way that we treat IBD. Here, we highlight the recent advances in using these technologies to evaluate IBD and discuss the ways that they can be leveraged to improve clinical outcomes.
نوع الوثيقة:	article in journal/newspaper
اللغة:	English
DOI:	10.1097/mog.0000000000000945
DOI:	10.1097/MOG.0000000000000945
الاتاحة:	http://dx.doi.org/10.1097/mog.0000000000000945 https://journals.lww.com/10.1097/MOG.0000000000000945
Rights:	http://creativecommons.org/licenses/by/4.0
رقم الانضمام:	edsbas.206EE2B5
قاعدة البيانات:	BASE

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الوصف
DOI:	10.1097/mog.0000000000000945