MUMBAI, India, Jan. 9 -- Intellectual Property India has published a patent application (202541133409 A) filed by Chaitanya Krishna Kasaraneni; and Sarmista Thalapaneni, Vijayawada, Andhra Pradesh, on Dec. 30, 2025, for 'ai-driven early-warning system for predicting multi-organ deterioration in critical care patients.'
Inventor(s) include Chaitanya Krishna Kasaraneni; and Sarmista Thalapaneni.
The application for the patent was published on Jan. 9, under issue no. 02/2026.
According to the abstract released by the Intellectual Property India: "The current idea proposes a multi-organ early-warning system based on artificial intelligence to predict deterioration across multiple organs in critically ill patients admitted to the intensive care unit. Current hospital monitoring tools mostly rely on threshold-based alerts, in which isolated physiological parameters are monitored and warnings are issued only when an evident deviation occurs. Such reactive processes delay clinical intervention, and in most cases, the onset of organ dysfunction occurs rapidly, rendering preventive therapy no longer possible. These limitations are overcome by the invention, which offers a continuously learning, context-aware predictive scheme that detects subtle trends and latent deterioration patterns well before the appearance of conventional clinical signs. The invention uses a layer-based system for data acquisition and fusion that combines real-time signals from bedside monitors, laboratory results, ventilator settings, medication history, and clinician-marked observations. By contrast with the evaluation of variables separately, this heterogeneous information is computed using a special modelling engine that makes interpretations of correlations among interdependent organ systems. The system uses the dynamics of time, cross-organ influence patterns, and baseline-specific to each patient to construct a quantified score of deterioration risk, which continuously changes with each incoming data stream. The innovation thus transforms the clinical process into continuous predictive surveillance rather than discontinuous evaluation. The system suggested includes a dynamic clinical interpretation module that puts the generated risk messages into perspective by considering the current plan of therapies being administered to the patient, comorbid conditions, and the past patterns of response. This module is aimed at optimizing predictive output, avoiding false alarms, and ensuring that alerts are related to meaningful changes in physiological stability. Once a critical limit is reached, the system sends an early-warning notification with a systematic explanation that details the systems that contribute to it, the trends that influence it, and approximate timelines for when it will escalate. This offers clinicians something to do at a time when it is still most beneficial to intervene. The invention, through its advanced modelling capabilities, assists care teams in avoiding unanticipated organ degeneration, optimizing treatment planning, and reducing mortality in intensive care settings. The system's predictive ability provides a revolutionary improvement over current triage and monitoring technologies, enabling earlier detection, more informed clinical decisions, and measurable improvements in patient outcomes. The invention is a highly scalable and realistic solution to contemporary critical-care management, seamlessly integrating with hospital information systems and disrupting clinical workflows."
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