Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Chaudhuri, Upasana; Chanda, Rishav; Sharma, Vandana; Mishra, Sushruta; Alkhyyat, Ahmed; Mishra, Nilamadhab Title A name given to the resource Personalized Medicine Recommendation Through Genomics AI Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2026 Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems;Volume;1386 LNNS;pp.39-53 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-981-96-6053-7_3" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-96-6053-7_3</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105019643445?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105019643445?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Chaudhuri U., Kalinga Institute of Industrial Technology, Bhubaneswar, India; Chanda R., Kalinga Institute of Industrial Technology, Bhubaneswar, India; Sharma V., Computer Science Department, CHRIST University, Bengaluru, India; Mishra S., Kalinga Institute of Industrial Technology, Bhubaneswar, India; Alkhyyat A., College of Technical Engineering, The Islamic University, Najaf, Iraq; Mishra N., VIT Bhopal University, Madhya Pradesh, Sehore, India Description An account of the resource Every individual is genetically different. This highlights the importance of exploring the possibility of personalized medicine tailored for each persons unique genetic profile. Due to this genetic variability, people have varied responses to the same medication. Thus, it is all the more necessary to withdraw from traditional medication and adopt personalized medicine. Using genomic data analysis techniques, healthcare specialists will be able to distinguish the minute genetic differences to produce unique therapies for each patient. This paper traverses the development of an algorithm to integrate the patients genomic data with his medical history. Personalized treatment can be recommended based on the inferences using genomic AI. These insights derived from the algorithm can be scrutinized by decision support systems. This step ensures the reliability of the prescribed personalized treatment and confidence of patients on the medication. Each time the model predicts medication compositions and dosages using genomic data, it becomes more accurate improving therapeutic results. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026. Subject The topic of the resource Data analysis; Genomic AI; Genomic data analysis; Machine learning; Personalized medicine Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Relation A related resource ISSN: 23673370; ISBN: 978-981966052-0; Language A language of the resource English Type The nature or genre of the resource Conference paper Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online