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Gopi Battineni is a researcher at University of Camerino in Camerino, Italy. He recently joined as post-doctoral position for Marche Biobank Project at School of Medicinal and Health Science Products in clinical research laborator in December 2021 to develop research based on simulation. He was previously doctoral student at the University of Camerino (2017-2020), where he conducted research on Telemedicine, Alzheimer’s disease prediction using Machine Learning models, Epidemic modelling, and development of ICT frameworks for seafarers. He worked with Nalini Chintalapudi and Getu Gamo Sagaro and under the direction of Francesco Amenta.

Research
His research focuses more generally on MRI image classification and AD prediction using demographic data with help of ML modeling.

He recently co-authored " Improved Alzheimer’s Disease Detection by MRI Using Multimodal Machine Learning Algorithms.

In the field of Telehealth, in 2021 he co-wrote with Getu Gamo Sagaro, Giulio Nittari, Nalini Chintalapudi, Graziano Pallotta and and Francesco Amenta the book chapter "Telehealth and Pharmacological Strategies of COVID-19 Prevention: Current and Future Developments.

He was chair of the ICAART 2020 at Malta, general chair of Bioimaging 2021. He is a member of the guest editorial board of Jounral of Personalized Medicine Journal, MDPI journal.

Publications
His most cited publications are:


 * Nalini Chintalapudi, Gopi Battineni, Francesco Amenta. COVID-19 virus outbreak forecasting of registered and recovered cases after sixty day lockdown in Italy: A data driven model approach. COVID-19. 2020 Jun;53(3):396-403. According to Google Scholar, this article has been cited 179 times
 * Giulio Nittari, Ravjyot Khuman, Simone Baldoni, Graziano Pallotta, Gopi Battineni, Ascanio Sirignano, Francesco Amenta, Giovanna Ricci. Telemedicine Practice: Review of the Current Ethical and Legal Challenges. Telemedicine. 2020 December;26(12):1427-1437. According to Google Scholar, this article has been cited 93 times
 * Gopi Battineni, Nalini Chintalapudi, Francesco Amenta. Machine learning in medicine: Performance calculation of dementia prediction by support vector machines (SVM). Machine Learning. 2019 June;16. According to Google Scholar, this article has been cited 59 times