AI in Genomics: Unlocking the Potential of Precision Medicine
Abstract
AI is revolutionizing genomics by enabling the analysis of vast genomic datasets to uncover disease mechanisms and therapeutic targets. This paper reviews AI applications in genome sequencing, variant annotation, and gene expression analysis. Challenges such as computational complexity, data privacy, and ethical concerns are discussed. The study highlights AI's role in advancing precision medicine by tailoring treatments to individual genetic profiles.
References
Davuluri, M. (2020). AI-Driven Predictive Analytics in Patient Outcome Forecasting for Critical Care. Research-gate journal, 6(6).
Davuluri, M. (2018). Revolutionizing Healthcare: The Role of AI in Diagnostics, Treatment, and Patient Care Integration. International Transactions in Artificial Intelligence, 2(2).
Vattikuti, M. C. (2020). A Comprehensive Review of AI-Based Diagnostic Tools for Early Disease Detection in Healthcare. Research-gate journal, 6(6).
Vattikuti, M. C. (2018). Leveraging Edge Computing for Real-Time Analytics in Smart City Healthcare Systems. International Transactions in Artificial Intelligence, 2(2).
Vattikuti, M. C. (2018). Leveraging AI for Sustainable Growth in AgTech: Business Models in the Digital Age. Transactions on Latest Trends in IoT, 1(1), 100-105.
Kolla, V. R. K. (2018). Forecasting the Future: A Deep Learning Approach for Accurate Weather Prediction. International Journal in IT & Engineering (IJITE).
Kolla, V. R. K. (2016). Analyzing the Pulse of Twitter: Sentiment Analysis using Natural Language Processing Techniques. International Journal of Creative Research Thoughts.
Kolla, V. R. K. (2015). Heart Disease Diagnosis Using Machine Learning Techniques In Python: A Comparative Study of Classification Algorithms For Predictive Modeling. International Journal of Electronics and Communication Engineering & Technology.
Kolla, V. R. K. (2020). Paws And Reflect: A Comparative Study of Deep Learning Techniques For Cat Vs Dog Image Classification. International Journal of Computer Engineering and Technology.
Kolla, V. R. K. (2016). Forecasting Laptop Prices: A Comparative Study of Machine Learning Algorithms for Predictive Modeling. International Journal of Information Technology & Management Information System.
Velaga, S. P. (2017). “ROBOTIC PROCESS AUTOMATION (RPA) IN IT: AUTOMATING REPETITIVE TASKS AND IMPROVING EFFICIENCY. IEJRD-International Multidisciplinary Journal, 2(6), 9.
Velaga, S. P. (2018). AUTOMATED TESTING FRAMEWORKS: ENSURING SOFTWARE QUALITY AND REDUCING MANUAL TESTING EFFORTS. International Journal of Innovations in Engineering Research and Technology, 5(2), 78-85.
Velaga, S. P. (2020). AIASSISTED CODE GENERATION AND OPTIMIZATION: LEVERAGING MACHINE LEARNING TO ENHANCE SOFTWARE DEVELOPMENT PROCESSES. International Journal of Innovations in Engineering Research and Technology, 7(09), 177-186.
Gatla, T. R. (2017). A SYSTEMATIC REVIEW OF PRESERVING PRIVACY IN FEDERATED LEARNING: A REFLECTIVE REPORT-A COMPREHENSIVE ANALYSIS. IEJRD-International Multidisciplinary Journal, 2(6), 8.
Gatla, T. R. (2019). A CUTTING-EDGE RESEARCH ON AI COMBATING CLIMATE CHANGE: INNOVATIONS AND ITS IMPACTS. INNOVATIONS, 6(09).
Gatla, T. R. “A GROUNDBREAKING RESEARCH IN BREAKING LANGUAGE BARRIERS: NLP AND LINGUISTICS DEVELOPMENT. International Journal of Creative Research Thoughts (IJCRT), ISSN, 2320-2882.
Gatla, T. R. (2018). AN EXPLORATIVE STUDY INTO QUANTUM MACHINE LEARNING: ANALYZING THE POWER OF ALGORITHMS IN QUANTUM COMPUTING. International Journal of Emerging Technologies and Innovative Research (www. jetir. org), ISSN, 2349-5162.
Gatla, T. R. MACHINE LEARNING IN DETECTING MONEY LAUNDERING ACTIVITIES: INVESTIGATING THE USE OF MACHINE LEARNING ALGORITHMS IN IDENTIFYING AND PREVENTING MONEY LAUNDERING SCHEMES (Vol. 6, No. 7, pp. 4-8). TIJER–TIJER–INTERNATIONAL RESEARCH JOURNAL (www. TIJER. org), ISSN: 2349-9249.
Pindi, V. (2018). NATURAL LANGUAGE PROCESSING(NLP) APPLICATIONS IN HEALTHCARE: EXTRACTING VALUABLE INSIGHTS FROM UNSTRUCTURED MEDICAL DATA. International Journal of Innovations in Engineering Research and Technology, 5(3), 1-10.
Pindi, V. (2019). A AI-ASSISTED CLINICAL DECISION SUPPORT SYSTEMS: ENHANCING DIAGNOSTIC ACCURACY AND TREATMENT RECOMMENDATIONS. International Journal of Innovations in Engineering Research and Technology, 6(10), 1-10.
DEEKSHITH, A. (2018). Seeding the Future: Exploring Innovation and Absorptive Capacity in Healthcare 4.0 and HealthTech. Transactions on Latest Trends in IoT, 1(1), 90-99.
DEEKSHITH, A. (2017). Evaluating the Impact of Wearable Health Devices on Lifestyle Modifications. International Transactions in Artificial Intelligence, 1(1).
DEEKSHITH, A. (2016). Revolutionizing Business Operations with Artificial Intelligence, Machine Learning, and Cybersecurity. International Journal of Sustainable Development in computer Science Engineering, 2(2).
DEEKSHITH, A. (2015). Exploring the Foundations, Applications, and Future Prospects of Artificial Intelligence. International Journal of Sustainable Development in computer Science Engineering, 1(1).
DEEKSHITH, A. (2014). Neural Networks and Fuzzy Systems: A Synergistic Approach. Transactions on Latest Trends in Health Sector, 6(6).
Boppiniti, S. T. (2019). Machine Learning for Predictive Analytics: Enhancing Data-Driven Decision-Making Across Industries. International Journal of Sustainable Development in Computing Science, 1(3).
Boppiniti, S. T. (2020). Big Data Meets Machine Learning: Strategies for Efficient Data Processing and Analysis in Large Datasets. International Journal of Creative Research In Computer Technology and Design, 2(2).
Adusumilli, S. B. K. Mitigating Cybersecurity Risks in Embedded Systems A Software-First Approach.
Sarkar, R., Malini, T. N., Adusumilli, S. B. K., Jena, M. S., & Patra, J. P. AI-INFUSED BLOCKCHAIN INNOVATIONS IN MANUFACTURING SUPPLY CHAINS FOR ECO-FRIENDLY PRACTICES TOWARDS A SUSTAINABLE FUTURE.