A Drug Recommendation System for Medical Emergencies using Machine Learning
DOI:
https://doi.org/10.48001/978-81-966500-2-5-5Keywords:
Drug , Image Procession , Pre-processing pipeline , Machine LearningAbstract
In wellbeing related crises, expeditious and exact medicine proposals are pivotal for patient perseverance and powerful treatment. This paper presents a Medication Thought Framework using man-made insight techniques to motorize and refresh drug choice during central clinical circumstances. To give exact medicine suggestions, the system processes broad patient information, like clinical chronicles and persistent prosperity markers. High precision and trustworthiness are ensured by the framework’s center, which is comprised of state of the art calculations for picture handling, include extraction, and order. A confusion organization is used to support the structure’s display, demonstrating its superiority to existing mental models and expanding its potential for emergency clinical consideration.
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