A Call for Deep learning in Healthcare

The concept of personalising patient care has a long history, and current advancements in diagnostic medical imaging and molecular medicine are slowly but steadily revolutionising healthcare services by providing information and diagnostic tools that allow for tailored patient treatment. Multiple he...

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Bibliographic Details
Published inTurkish journal of computer and mathematics education Vol. 12; no. 12; pp. 2711 - 2713
Main Authors Gupta, Chabi, Singh, Preeti, Bhatia, Swati
Format Journal Article
LanguageEnglish
Published Trabzon Karadeniz Technical University Distance Education Research and Application Center 01.01.2021
Subjects
Customization
Deep learning
Health care
Health services
Medical imaging
Medicine
Precision medicine
Prediction models
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Summary:The concept of personalising patient care has a long history, and current advancements in diagnostic medical imaging and molecular medicine are slowly but steadily revolutionising healthcare services by providing information and diagnostic tools that allow for tailored patient treatment. Multiple heterogeneous elements, such as socio-demographics, gene variability, environmental, and lifestyle factors, must be considered in order to facilitate personalized/precision treatment. As a result, one of the most pressing difficulties in personalised medicine is transforming enormous amounts of multimodal data into decision support tools capable of bridging the gap between research and clinical practise.Deep learning (DL) provides a unique answer to these issues, allowing for the acquisition or building of high-accuracy, multi-modal prediction models that will soon enable the realisation of the personalised medicine vision.
ISSN:1309-4653