The pandemic of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is spreading all over the world. Medical health care systems are in urgent need to diagnose this pandemic with the support of new emerging technologies like artificial intelligence (AI), internet of things (IoT) and Big Data System. In this dichotomy study, we divide our research in two ways—firstly, the review of literature is carried out on databases of Elsevier, Google Scholar, Scopus, PubMed and Wiley Online using keywords Coronavirus, Covid-19, artificial intelligence on Covid-19, Coronavirus 2019 and collected the latest information about Covid-19. Possible applications are identified from the same to enhance the future research. We have found various databases, websites and dashboards working on real time extraction of Covid-19 data. This will be conducive for future research to easily locate the available information. Secondly, we designed a nested ensemble model using deep learning methods based on long short term memory (LSTM). Proposed Deep-LSTM ensemble model is evaluated on intensive care Covid-19 confirmed and death cases of India with different classification metrics such as accuracy, precision, recall, f-measure and mean absolute percentage error. Medical healthcare facilities are boosted with the intervention of AI as it can mimic human intelligence. Contactless treatment is possible only with the help of AI assisted automated health care systems. Furthermore, remote location self treatment is one of the key benefits provided by AI based systems.

严重急性呼吸系统综合症冠状病毒 2 (SARS-CoV-2) 的大流行正在全世界蔓延。医疗保健系统迫切需要在人工智能 (AI)、物联网 (IoT) 和大数据系统等新兴技术的支持下诊断这种流行病。在这个二分法研究中，我们以两种方式划分我们的研究——首先, 使用关键词冠状病毒、Covid-19、Covid-19 上的人工智能、冠状病毒 2019 对 Elsevier、Google Scholar、Scopus、PubMed 和 Wiley Online 的数据库进行文献回顾，并收集有关 Covid-19 的最新信息。从中确定可能的应用程序以增强未来的研究。我们发现了各种用于实时提取 Covid-19 数据的数据库、网站和仪表板。这将有利于未来的研究轻松定位可用信息。其次，我们使用基于长短期记忆（LSTM）的深度学习方法设计了一个嵌套集成模型。提出的 Deep-LSTM 集成模型对印度的重症监护 Covid-19 确诊病例和死亡病例进行了评估，具有不同的分类指标，例如准确度、精确度、召回率、f 度量和平均绝对百分比误差。医疗保健设施在人工智能的干预下得到了提升，因为它可以模仿人类的智能。只有在人工智能辅助的自动化医疗保健系统的帮助下，才能实现非接触式治疗。此外，远程位置自我治疗是基于人工智能的系统提供的主要优势之一。