Dengue, a mosquito-borne viral fever, causes an epidemic that impacts 39 crore cases annually around the globe with 5,00,000 cases causing severe illness resulting in about 25,000 annual deaths. It has prevailed in India since the late 1960s and today, the state of Uttar Pradesh is witnessing its worst outbreak in decades. Due to a lack of vaccines and antivirals, the prevention of Dengue is dependent on controlling the species of mosquitoes that cause it, namely the Aedes mosquito. This is done through methods like chemical intervention, Habitat management and Genetic techniques to name a few. Today, a new development in this field of research has been made by a young Indian Doctor-Scientist, Dr. Abhijit Ray, who has come up with an AI/ML based solution, that helps deal with the seriousness of Dengue and removes uncertainty, helping Administration, Doctors and Patient/Patient Party.
Dengue fever in itself, especially the severe cases of Dengue, have been challenging for researchers and the underlying complexities of the illness are yet to be fully understood. Severe cases of Dengue which lead to fatalities are caused due to hemorrhagic shock caused by a phenomenon that is known as thrombocytopenia induced bleeding. What this means is that the blood platelet count in the body reaches a very low level which then does not allow the required oxygen and nutrients to reach cells in our bodies to carry out basic functions. This is described as the cell being in a state of shock. In the case of Dengue, this is known as Dengue Shock Syndrome or DSS. DSS is what causes deaths in the cases of severe Dengue fever.
The relationship between the loss of blood platelets and when it results in severe Dengue Shock Syndrome has been tough to clearly determine. This means that physicians across the world have found it difficult to predict the patients that would succumb to DSS, and its diagnosis is often too late. This has now changed with the new study by Dr. Abhijit. This study is aimed to predict Dengue Shock Syndrome using the approach of Machine learning and Artificial Intelligence. The resultant software of this study is now successfully able to make this prediction in a relatively early stage of Dengue patients who would potentially suffer with DSS.
The software uses Blood Platelets (PLT) count and Hematocrit (HCT) levels. The AI based algorithm is able to accurately determine with the PLT and HCT from the third day of a patient having Dengue fever, the probability of a patient later on having DSS. This breakthrough in science which helps in the accurate prediction of DSS influences the way at-risk patients are treated and allows medical workers to monitor and treat patients with Dengue with far more care, help planning treatment and reduce the mortality rate of Dengue fever related deaths. This comes at a time when hospitals in states like Uttar Pradesh are frantically battling Dengue. This new development can aid in averting further Dengue related crisis situations.
Dr Abhijit, enabled by FITTO Patient Management, were able to make this breakthrough.
