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ARTIFICIAL INTELLIGENCE IN BIOINFORMATICS: ENHANCING ANALYSIS

Dr. Bhavna Bajpai is a highly accomplished and experienced professional in the field of Information Technology and Computer Science Application Department. As the Dean and IQAC Coordinator at Dr. C. V. Raman University in Khandwa, Madhya Pradesh, India, she has established herself as a seasoned expert with over 18 years of experience. Dr. Bajpai’s impressive academic credentials include a Bachelor’s degree in Computer Science, a Post Graduate diploma in Computer Science and Application, a Master’s in Information Technology, and a Ph.D. in Computer Science and Application. She is an esteemed member of numerous international and national professional organizations and has authored several research papers that have been published in prestigious IEEE/Springer Conferences, Scopus/SCIE Journals, and National and International Journals. Her contributions to the field have earned her several awards.

Dr. Vishwanath Savanur, working as an Assistant Professor, Dept. of Mathematics, Sri Sairam College of engineering, Bangalore, India. I completed my Ph.D. in Applied Mathematics from Vijayanagara Sri Krishnadevara University, Ballari, Karnataka, INDIA. My research interest includes Theoretical and Computational Fluid Dynamics, Magnetohydrodynamics, Rotating Fluids, Heat and Mass Transfer etc. I have published ten research articles in international/national journal of reputes.

Dr. Bharat Kaushik is an accomplished healthcare business leader and has published various whitepapers in the healthcare space in areas like Telehealth, Impact of digitalization on E-Health services. He has participated in various Healthcare conferences including HIMSS India. Dr. Bharat did his Ph.D (H.C.) in Healthcare Management from USA, Master’s degree in Biotechnology from USA and B.Tech. in Biotechnology from India. He is PAHM® designated and is CSPO ®, Prince 2 certified.

Dr. Haewon Byeon received the Dr Sc degree in Biomedical Science from Ajou University School of Medicine. Haewon Byeon currently works at the Department of Medical Big Data, Inje University. His recent interests focus on health promotion, AI-medicine, and biostatistics. He is currently a member of international committee for a Frontiers in Psychiatry, and an editorial board for World Journal of Psychiatry. Also, He were worked on 4 projects (Principal Investigator) from the Ministry of Education, the Korea Research Foundation, and the Ministry of Health and Welfare. Byeon has published more than 343 articles and 19 books.

 

 

Description

Artificial Intelligence (AI) has emerged as a transformative force in the field of bioinformatics, revolutionizing the way biological data is analyzed, interpreted, and utilized. By harnessing machine learning algorithms, AI empowers researchers to extract meaningful insights from vast amounts of genomic, proteomic, and metabolomic data, enabling advancements in areas such as disease diagnosis, drug discovery, and personalized medicine. AI-driven approaches excel in identifying complex patterns, uncovering hidden relationships, and predicting biological phenomena with unprecedented accuracy. Moreover, AI facilitates the integration of multi-omics data, bridging the gap between different layers of biological information to provide a holistic understanding of biological systems. Through innovative techniques such as deep learning, reinforcement learning, and natural language processing, AI continues to push the boundaries of bioinformatics, paving the way for novel discoveries and transformative applications in healthcare and beyond. AI-driven bioinformatics tools and algorithms are enhancing our understanding of the intricate mechanisms underlying diseases, allowing for the development of targeted therapies and precision medicine approaches. These advancements enable clinicians to tailor treatments to individual patients based on their unique genetic makeup, leading to more effective interventions and improved patient outcomes. Additionally, AI is playing a crucial role in drug repurposing by rapidly identifying existing medications that could be repurposed to treat new diseases or conditions, accelerating the drug development process and reducing costs. Moreover, AI-powered predictive models are being leveraged to forecast disease outbreaks, anticipate drug resistance patterns, and optimize healthcare resource allocation, thereby enhancing public health efforts and mitigating potential crises. As AI continues to evolve and integrate with bioinformatics, its impact on healthcare and biomedical research is poised to grow exponentially, offering unprecedented opportunities to unravel the complexities of life and revolutionize the practice of medicine

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