Guardianseps: Empowering Early Sepsis Detection
Sepsis is one of the utmost significant cares in healthcare that requires immediate detection for effective treatment. GuardianSeps, an innovative Deep Learning-based system, that integrates various patient data sources including the laboratory investigations, physician's notes, and physical assessment findings. Extracted signs from Electronic Health Records (EHR). This is because GuardianSeps comprehensive approach involved data collection, data cleaning and pre-processing, feature selection/extraction, modelling/prediction phase, evaluation, and deployment. Continuous monitoring and feedback loops are highlighted so that this system can be easily developed durability and ease of use particularly in the clinical field. GuardianSeps emphasizes the cooperation of physicians, statisticians, and Artificial intelligence technologies experts to advance ethical skills in health care. While with awareness of issues related to it such as interpretability of the results and the data. Biases, the focus is to reductionism of the complex phenomena and upholding ethical standards. The ongoing refinement of GuardianSeps has quite an aura of committed to improving patient for delivery the care through change management and innovation. By administering cooperation and embedding feedback GuardianSeps has the primary goal to consider new trends and enhance its efficiency as a way to address sepsis, in the long run to enhance the quality of health care and perhaps even save lives GuardianSeps therefore has methods of ensuring patient's privacy and protection of their data applying measures to protect certain kind of health information during the whole process of NLID detection. This Adherence to the policies of protecting data develop confidence among patients and healthcare providers, recommending communities the use of these innovations of the system. With advances in medical science and with the use of modern technology as innovations occur, GuardianSeps continues to be responsive, and sophisticated its usefulness to the current society and its capacities to address the current social problems to collectively address sepsis as well as other significant health care breakthroughs.
Authors
- K Antony Kumar (ORCID: https://orcid.org/0000-0001-7409-4220)
- S. Niresh Kumar
- Charan Appala
- Shreya Balurgi
- Praveen Royal Balaiahgari
- Jerlin Francy Rajan (ORCID: https://orcid.org/0009-0004-7339-0211)
Institutions
- Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology (IN)
- St. Joseph's Institute of Technology (IN)
Publication Details
- Published
- 2025-03-27
- DOI
- https://doi.org/10.1109/icfts62006.2025.11031943
- Primary Topic
- Sepsis Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00