A Call for Deep learning in Healthcare
Main Article Content
Abstract
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.
Downloads
Metrics
Article Details
Licensing
TURCOMAT publishes articles under the Creative Commons Attribution 4.0 International License (CC BY 4.0). This licensing allows for any use of the work, provided the original author(s) and source are credited, thereby facilitating the free exchange and use of research for the advancement of knowledge.
Detailed Licensing Terms
Attribution (BY): Users must give appropriate credit, provide a link to the license, and indicate if changes were made. Users may do so in any reasonable manner, but not in any way that suggests the licensor endorses them or their use.
No Additional Restrictions: Users may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
