MUMBAI, India, June 24 -- Intellectual Property India has published a patent application (202441095966 A) filed by Sheffalli R; Shwethaa G; Sujithra S; Hansanandhini Ru; and Laksita V S on December 05, 2024, for Predictive Model For Multiple Myeloma Leveraging Machine Learning And Biomarker Data For Early Detec.
Inventors include Sheffalli R; Shwethaa G; Sujithra S; Hansanandhini Ru; and Laksita V S.
The application for the patent was published on June 12, 2026, under issue no. 24/2026.
Abstract: Using machine learning algorithms and multimodal biomarker data, this innovation offers a novel prediction model for the early diagnosis of multiple myeloma. The model provides a thorough examination of patient health by combining genetic, proteomic, and clinical biomarkers, allowing for early disease identification. Its capacity to absorb intricate, multifaceted data and spot patterns that conventional diagnostic techniques frequently overlook is what makes it innovative. By customising its predictions to each biomarker profile, our predictive approach enhances the precision and dependability of early detection while personalising risk assessments. In comparison to current models, the machine learning methods used in this invention greatly increase detection accuracy by utilising sophisticated feature extraction techniques. The methodology offers"a proactive approach to patient monitoring and treatment by dynamically updating risk estimates based on ongoing analysis of real- time biomarker data. Applicability across a range of clinical situations and demographics is guaranteed by its scalable design. The main goals of the invention are to reduce healthcare expenditures, enable earlier intervention, and lessen the need for late-stage treatments in order to enhance clinical outcomes. All things considered, by tackling significant issues with existing diagnostic techniques, our prediction model marks a significant breakthrough in multiple myeloma early diagnosis and personalised medication
Disclaimer: Curated by HT Syndication.
