Mucormycosis is a rare but a life-threatening fungal infection. India has been facing a public health challenge from COVID-19 related mucormycosis. A collaborative study aimed at developing artificial intelligence-based models to predict the risk of mucormycosis among the patients at the time of discharge from hospital.  The dataset included 1229 COVID-19 positive patients and 214 inpatients, COVID-19 positive and infected with mucormycosis. The authors used logistic regression, decision tree, random forest, and the extreme gradient boosting algorithm. All the models were evaluated with 5-fold validation to derive a reliable estimate of the model error. The study determined that the top five variables positively impacted mucormycosis risk positively impacted obesity, anosmia, de novo diabetes, myalgia, and nasal discharge. The developed model can predict the patients at high risk, thus initiating preventive care or aiding in the early detection of mucormycosis infection. Thus, this study holds potential for early treatment and better management of patients suffering from COVID-19-associated mucormycosis.


Prof. B Raja Shekhar                                                Prof. GVRK Acharyulu

Prof. Raja Shekhar Bellamkonda and Prof. GVRK Acharyulu from the School of Management Studies, University of Hyderabad, India; Prof. Shabbir Syed Abdul, Prof. Jack and Shwetambara from Taipei Medical University, Taiwan; Prof. A. Shoban Babu, Dr. Naresh, and Mr. Venkata Ramana from Gandhi Medical College and Hospital, Secunderabad, India;  Dr. Ramaiah Itumalla (did Ph.D. with Prof. Raja Shekhar Bellamkonda and Prof. GVRK Acharyulu), University of Hail, Saudi Arabia and Mr. Surya, Data Scientist, iQGateway, Bengaluru, Karnataka, have developed Artificial Intelligence-based models to predict the risk of mucormycosis among the patients at the time of discharge from hospital. The study was published in the Journal of Infection (an official journal of the British Infection Association), with a high impact factor of 38.63.

Area under receiver operating characteristic curve (AUROC) for the models developed in the study.

Prof. Raja Shekhar, one of the co-authors, says that applying technology and mathematical models will be crucial for the growth of the healthcare sector. Prof. Shabbir expresses that the appropriate use of Artificial Intelligence in healthcare can benefit us in this challenging pandemic situation. There is a need for more collaborative research work in the healthcare domain, Prof. GVRK Acharyulu (mentor of MBA Healthcare and Hospital Management program at SMS) has added.