Hyderabad varsity researchers develop AI models to predict Mucormycosis

Hyderabad: Researchers from the University of Hyderabad (UoH) along with other researchers have developed artificial intelligence-based models to predict the risk of the rare but life-threatening fungal infection, Mucormycosis, among Covid-19 patients at the time of discharge from the hospital. The collaborative study included a dataset of 1,229 Covid-19 positive patients and 214 inpatients, Covid-19 […]

Hyderabad: Researchers from the University of Hyderabad (UoH) along with other researchers have developed artificial intelligence-based models to predict the risk of the rare but life-threatening fungal infection, Mucormycosis, among Covid-19 patients at the time of discharge from the hospital.

The collaborative study included a dataset of 1,229 Covid-19 positive patients and 214 inpatients, Covid-19 positive and infected with Mucormycosis. The study found the top five variables that impacted Mucormycosis risk were obesity, anosmia, de novo diabetes, myalgia and nasal discharge.

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According to the researchers, the developed models could predict the patients at high risk, thus initiating preventive care or aiding in early detection of Mucormycosis. The study holds potential for early treatment and better management of patients suffering from Covid-19-associated Mucormycosis, they said.

The models were developed by Prof. Raja Shekhar Bellamkonda and Prof. GVRK Acharyulu from the School of Management Studies, UoH; Prof. Shabbir Syed Abdul, Prof. Jack and Shwetambara from Taipei Medical University, Taiwan; Prof. A Shoban Babu, Dr. Naresh, and Venkata Ramana from Gandhi Medical College and Hospital; Dr. Ramaiah Itumalla, University of Hail, Saudi Arabia and Surya, Data Scientist, iQGateway, Bengaluru, Karnataka.

The study was published in the Journal of Infection, an official journal of the British Infection Association.