October 2024
Intermediate to advanced
560 pages
14h 37m
English
book
Genomics at the Nexus of AI, Computer Vision, and Machine Learning
by Shilpa Choudhary, Sandeep Kumar, Swathi Gowroju, Monali Gulhane, R. Sri Lakshmi
Content preview from Genomics at the Nexus of AI, Computer Vision, and Machine Learning
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19Decoding the Future: COVID-19 RNA Sequence Prediction Through LSTM Transformation
M.D. Khaja Shaik1, K. Narsimhulu2, B.V.N. Praveena3*, Sarita Dabur4 and G. Pratyusha3
1Department of ECE, SACET, Hyderabad, India
2Department of CSE, Matrusri Engineering College, Hyderabad, India
3Department of CSE, DVR & Dr. HS MIC College of Technology, Vijayawada, India
4Department of Law, Bahadurgarh Court, Haryana, India
Abstract
This work presents an innovative method for forecasting the daily recuperation of COVID-19 patients, providing a new viewpoint to enhance treatment techniques. Our methodology differs from traditional approaches by not only considering the overall count of COVID-19 cases or deaths, but also by estimating the number of recoveries. This approach offers useful insights into the progression of the disease and assists in making well-informed decisions on patient care. Instead of using typical time series models, we utilise a multilayer perceptron (MLP) framework with various inputs to predict the daily recovery figures. This deviation enables intricate comprehension of the mechanics of recovery, empowering healthcare providers to customise treatment approaches according to emerging patterns. In addition, we determine the most essential factors for predicting COVID-19 recoveries by utilising the correlation method and investigating causal connections. This research facilitates the identification of the key factors that have a substantial impact on the recovery process, ...
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