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How artificial intelligence may help the Covid-19 pandemic: Pitfalls and lessons for the future.
Malik, Yashpal Singh; Sircar, Shubhankar; Bhat, Sudipta; Ansari, Mohd Ikram; Pande, Tripti; Kumar, Prashant; Mathapati, Basavaraj; Balasubramanian, Ganesh; Kaushik, Rahul; Natesan, Senthilkumar; Ezzikouri, Sayeh; El Zowalaty, Mohamed E; Dhama, Kuldeep.
Afiliação
  • Malik YS; Division of Biological Standardization, ICAR-Indian Veterinary Research Institute, Bareilly, Uttar Pradesh, India.
  • Sircar S; College of Animal Biotechnology, Guru Angad Dev Veterinary and Animal Sciences University, Ludhiana, Punjab, India.
  • Bhat S; Division of Biological Standardization, ICAR-Indian Veterinary Research Institute, Bareilly, Uttar Pradesh, India.
  • Ansari MI; Division of Biological Standardization, ICAR-Indian Veterinary Research Institute, Bareilly, Uttar Pradesh, India.
  • Pande T; Division of Biological Standardization, ICAR-Indian Veterinary Research Institute, Bareilly, Uttar Pradesh, India.
  • Kumar P; Division of Biological Standardization, ICAR-Indian Veterinary Research Institute, Bareilly, Uttar Pradesh, India.
  • Mathapati B; Amity Institute of Virology and Immunology, Amity University, Noida, Uttar Pradesh, India.
  • Balasubramanian G; Polio Virus Group, Microbial Containment Complex, I.C.M.R. National Institute of Virology, Pune, Maharashtra, India.
  • Kaushik R; Laboratory Division, Indian Council of Medical Research -National Institute of Epidemiology, Ministry of Health & Family Welfare, Chennai, Tamil Nadu, India.
  • Natesan S; Laboratory for Structural Bioinformatics, Center for Biosystems Dynamics Research, RIKEN, Yokohama, Kanagawa, Japan.
  • Ezzikouri S; Indian Institute of Public Health Gandhinagar, Gandhinagar, Gujarat, India.
  • El Zowalaty ME; Viral Hepatitis Laboratory, Virology Unit, Institut Pasteur du Maroc, Casablanca, Morocco.
  • Dhama K; Department of Clinical Sciences, College of Medicine, University of Sharjah, Sharjah, UAE.
Rev Med Virol ; 31(5): 1-11, 2021 09.
Article em En | MEDLINE | ID: mdl-33476063
The clinical severity, rapid transmission and human losses due to coronavirus disease 2019 (Covid-19) have led the World Health Organization to declare it a pandemic. Traditional epidemiological tools are being significantly complemented by recent innovations especially using artificial intelligence (AI) and machine learning. AI-based model systems could improve pattern recognition of disease spread in populations and predictions of outbreaks in different geographical locations. A variable and a minimal amount of data are available for the signs and symptoms of Covid-19, allowing a composite of maximum likelihood algorithms to be employed to enhance the accuracy of disease diagnosis and to identify potential drugs. AI-based forecasting and predictions are expected to complement traditional approaches by helping public health officials to select better response and preparedness measures against Covid-19 cases. AI-based approaches have helped address the key issues but a significant impact on the global healthcare industry is yet to be achieved. The capability of AI to address the challenges may make it a key player in the operation of healthcare systems in future. Here, we present an overview of the prospective applications of the AI model systems in healthcare settings during the ongoing Covid-19 pandemic.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Atenção à Saúde / COVID-19 Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: Rev Med Virol Assunto da revista: VIROLOGIA Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Índia

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Atenção à Saúde / COVID-19 Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: Rev Med Virol Assunto da revista: VIROLOGIA Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Índia