Division of Biological Standardization, ICAR-Indian Veterinary Research Institute, Bareilly, Uttar Pradesh, India.
College of Animal Biotechnology, Guru Angad Dev Veterinary and Animal Sciences University, Ludhiana, Punjab, India.
Rev Med Virol. 2021 Sep;31(5):1-11. doi: 10.1002/rmv.2205. Epub 2020 Dec 19.
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.
由于 2019 年冠状病毒病 (Covid-19) 的临床严重程度、快速传播和人员损失，世界卫生组织宣布其为大流行。传统的流行病学工具正得到人工智能 (AI) 和机器学习等最新创新的显著补充。基于人工智能的模型系统可以提高对人群中疾病传播模式的识别和对不同地理位置暴发的预测。Covid-19 的症状和体征可用的数据数量很少且不稳定，这允许采用最大似然算法的组合来提高疾病诊断的准确性，并识别潜在的药物。预计基于人工智能的预测和预测将通过帮助公共卫生官员选择针对 Covid-19 病例的更好应对和准备措施来补充传统方法。基于人工智能的方法已经帮助解决了关键问题，但尚未对全球医疗保健行业产生重大影响。人工智能解决这些挑战的能力可能使其成为未来医疗保健系统运作的关键参与者。在这里，我们概述了在当前的 Covid-19 大流行期间，人工智能模型系统在医疗保健环境中的预期应用。
