##plugins.themes.bootstrap3.article.main##

Bandar Mashan Madhhur Alshammari , Marzouq Ghannam Mohamed Alrashdi , Abdullatif Fehaid J Alshammari , Mohammed Nawi Jadaan , Huda Fayez F Alshammari, Salman Ghafil S Alshammari , Saleh Mohammad A Almalaq , Hala Akhil Khadir Alshammari , Ahmed Mashi Al Reshidi , Abdulrahman Saud Alreshidi

Abstract

With rapid advancements in data capture, data storage, and computer processing capabilities, it is now possible to consider "real-world" medical imaging data and the associated clinical information in the development of artificial systems that support clinical decision-making. As a predictive tool, the focus of AI (and AI research) is to provide prediction to support the most effective patient management. Ideally, in the future, there is the possibility that decisions to treat could be supported by a more precise prediction of outcomes. For example, modern imaging can detect subtle abnormalities in the brain and label patients with the potential for mild cognitive impairment. However, the rate of progression to dementia varies considerably in this group. AI methods could be used to define those patients at highest risk of progressive disease (using changes in serial imaging and clinical monitoring) and thus inform decisions about early intervention tailored for this risk group. This broad scope could be used to tailor prediction models for individual disease processes that define the likelihood of specific diagnoses or outcomes and potential responses to treatments. In defining any of these decision tasks, AI requires vast data knowledge of the disease process in question. Prediction today in most clinical conditions is based on expert opinion, often using simple probability estimation without reference to specific patient variables. Thus, there is an opportunity for a knowledge discovery step using existing health datasets to define the decision task and enable a model that predicts individual patient risk and potential expected treatment responses.

Metrics

Metrics Loading ...

##plugins.themes.bootstrap3.article.details##

Section
Articles

How to Cite

Artificial Intelligence In Medical Imaging. (2022). Journal of Namibian Studies : History Politics Culture, 31(Special Issue 3), 1355-1371. https://doi.org/10.59670/xyqbqa58