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Pitfalls and lesson...
Pitfalls and lessons for the future : Pitfalls and lessons for the future
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- Malik, Yashpal Singh (author)
- ICAR Indian Vet Res Inst, Div Biol Standardizat, Bareilly, Uttar Pradesh, India.;Guru Angad Dev Vet & Anim Sci Univ, Coll Anim Biotechnol, Ludhiana, Punjab, India.
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- Sircar, Shubhankar (author)
- ICAR Indian Vet Res Inst, Div Biol Standardizat, Bareilly, Uttar Pradesh, India.
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- Bhat, Sudipta (author)
- ICAR Indian Vet Res Inst, Div Biol Standardizat, Bareilly, Uttar Pradesh, India.
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- Ansari, Mohd Ikram (author)
- ICAR Indian Vet Res Inst, Div Biol Standardizat, Bareilly, Uttar Pradesh, India.
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- Pande, Tripti (author)
- ICAR Indian Vet Res Inst, Div Biol Standardizat, Bareilly, Uttar Pradesh, India.
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- Kumar, Prashant (author)
- Amity Univ, Amity Inst Virol & Immunol, Noida, Uttar Pradesh, India.
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- Mathapati, Basavaraj (author)
- ICMR Natl Inst Virol, Polio Virus Grp, Microbial Containment Complex, Pune, Maharashtra, India.
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- Balasubramanian, Ganesh (author)
- Minist Hlth & Family Welf, Lab Div, Indian Council Med Res, Natl Inst Epidemiol, Chennai, Tamil Nadu, India.
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- Kaushik, Rahul (author)
- RIKEN, Lab Struct Bioinformat, Ctr Biosyst Dynam Res, Yokohama, Kanagawa, Japan.
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- Natesan, Senthilkumar (author)
- Indian Inst Publ Hlth Gandhinagar, Gandhinagar, Gujarat, India.
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- Ezzikouri, Sayeh (author)
- Inst Pasteur Maroc, Virol Unit, Viral Hepatitis Lab, Casablanca, Morocco.
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- El Zowalaty, Mohamed E. (author)
- Uppsala universitet,Institutionen för medicinsk biokemi och mikrobiologi,Univ Sharjah, Coll Med, Dept Clin Sci, Sharjah, U Arab Emirates.
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- Dhama, Kuldeep (author)
- ICAR Indian Vet Res Inst, Div Pathol, Bareilly, Uttar Pradesh, India.
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ICAR Indian Vet Res Inst, Div Biol Standardizat, Bareilly, Uttar Pradesh, India;Guru Angad Dev Vet & Anim Sci Univ, Coll Anim Biotechnol, Ludhiana, Punjab, India. ICAR Indian Vet Res Inst, Div Biol Standardizat, Bareilly, Uttar Pradesh, India. (creator_code:org_t)
- 2020-12-19
- 2021
- English.
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In: Reviews in Medical Virology. - : John Wiley & Sons. - 1052-9276 .- 1099-1654. ; 31:5
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Abstract
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- 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 responses 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.
Subject headings
- MEDICIN OCH HÄLSOVETENSKAP -- Hälsovetenskap -- Folkhälsovetenskap, global hälsa, socialmedicin och epidemiologi (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Health Sciences -- Public Health, Global Health, Social Medicine and Epidemiology (hsv//eng)
Keyword
- artificial intelligence
- covid-19
- epidemiology
- diagnosis
- SARS-CoV-2
- therapeutic developments
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Malik, Yashpal S ...
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Sircar, Shubhank ...
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Bhat, Sudipta
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Ansari, Mohd Ikr ...
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Pande, Tripti
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Kumar, Prashant
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Mathapati, Basav ...
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Balasubramanian, ...
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Kaushik, Rahul
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Natesan, Senthil ...
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Ezzikouri, Sayeh
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El Zowalaty, Moh ...
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Dhama, Kuldeep
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Uppsala University