FindD: AI-Driven Insights for Bone and Muscle Deficiencies Across Generations

Abstract

This literature review examines a novel strategy for treating vitamin deficiencies, with a focus on vitamin D, vitamin K, and vitamin E. It also highlights the importance of deficiency of the vitamin D&K for bone and the vitamin E for muscle abnormalities in children and adults. The research uses an extensive methodology that combines deep learning-based image processing techniques with machine learning for text-based question-and-answer(Q&A) engagements. Through conversation, users are able to provide pertinent details about symptoms. Machine learning algorithms are then used to analyse the collected data. Concurrently, relevant images are processed by deep learning models to uncover subtle patterns that point to certain vitamin deficiencies. In order to address issues with bone caused by vitamin deficiencies, this research attempts to provide insights into the nexus of machine learning and deep learning for personalized diagnosis of vitamin deficiencies. The comprehensive method takes into account the multiplicity of variables affecting vitamin levels and how they affect bone health across age groups. This study's keywords are deep learning image processing, Q&A-based machine learning, vitamin D, vitamin K, and vitamin E deficiencies, as well as bone abnormalities.