MUMBAI, India, Sept. 14 -- Intellectual Property India has published a patent application (202641095136 A) filed by Dr. Venkatesan C; Dr. V. Balaji Vijayan; Dr. Sharavana K; Dr. R. Dinesh; and Madhusudhana V on August 06, 2026, for Data-Driven Prediction Of Acute Respiratory Syndrome Progression Using Machine Learning Algorithms.
Inventors include Dr. Venkatesan C; Dr. V. Balaji Vijayan; Dr. Sharavana K; Dr. R. Dinesh; and Madhusudhana V.
The application for the patent was published on September 11, 2026, under issue no. 37/2026.
Abstract: Abstract: ARS (acute respiratory syndrome) is a serious respiratory condition that can harm the lungs or other respiratory organs. From moderate to severe, ARS signs can include chest discomfort, cough, fever, and difficulty breathing. Life-threatening ARS complications may necessitate extensive medical care. It happens whenever the lungs are unable to expel sufficient carbon dioxide or provide the body with adequate oxygen. Widespread infections caused by it have the potential to harm tissues and organs throughout the body.Acute respiratory distress syndrome (ARDS) occurs whenever the lungs swell up with fluid and experience significant inflammation. It can render breathing challenging and may result in breathlessness, heavy breathing, and insufficient oxygen levels in the blood. Mechanical ventilation and palliative therapy, including oxygen therapy and anti-inflammatory drugs, are frequently used in the treatment of ARDS.Machine learning techniques may be applied to provide an in-depth analysis of the course of acute respiratory diseases. Using medical and epidemiologic data, machine learning has become an effective method for predicting and classifying the various types of ARS. Machine learning is an effective method for forecasting and analyzing ARS development. Machine learning systems can detect early warning symptoms of severe ARS and improve patient outcomes by examining large datasets with patient records. Keywords:ARS (acute respiratory syndrome), Machine learning, Respiratory Conditions
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