认知计算系统是智能系统，通过将人工智能、机器学习和自然语言处理等技术融合，可以思考、理解和增强人类大脑的能力。近年来，通过预防、预测和分析疾病来维护或提高健康状况已成为一项具有挑战性的任务。日益增多的疾病及其原因已成为人类面临的重大问题。认知计算存在风险分析有限、繁琐的培训过程和自动化的关键决策等问题。为解决这个问题，医疗保健领域的认知计算就像医疗神童一样，预测人类的疾病或疾病，并帮助医生采取及时行动。本文的主要目的是探讨认知计算在医疗保健中的现有和未来技术趋势。文章回顾了不同的认知计算应用，并推荐最佳应用给临床医生。基于这个建议，医生能够监测和分析患者的身体健康状况。本文提供了认知计算在医疗保健领域的系统文献综述。共筛选了SCOPUS、IEEE Xplore、Google Scholar、DBLP、Web of Science、Springer和PubMed等七个在线数据库，并收集了2014年至2021年发布的有关认知计算在医疗保健领域的文章。总共选择了75篇文章，并对其优点和缺点进行了分析。根据系统综述和Meta分析（PRISMA）指南，进行了分析。这篇综述文章的基本发现及其对理论和实践的重要性是认知计算平台、认知应用于医疗保健和认知计算在医疗保健中的使用案例绘制的思维导图。详细的讨论部分重点介绍了当前问题、未来研究方向和认知计算在医疗保健中的最新应用。对不同认知系统的准确度分析表明，医用筛子达到0.95，而用于肿瘤的Watson（WFO）达到0.93，因此成为医疗保健中突出的计算系统。认知计算是医疗保健领域中不断发展的技术，可以增强临床思维过程，让医生做出正确的诊断并保持病人的健康状况良好。这些系统能够提供及时的护理、最佳和经济有效的治疗。本文通过强调平台、技术、工具、算法、应用和使用案例，全面调查了认知计算在健康领域中的重要性。本综述还探讨了现有问题的文献作品，并提出了未来在医疗保健领域应用认知系统的研究方向。版权所有©2023 Elsevier B.V.。

Cognitive Computing systems are the intelligent systems that thinks, understands and augments the capabilities of human brain by blending the technologies of Artificial Intelligence, Machine Learning and Natural Language Processing. In recent days, maintenance or enhancement of health by preclusion, prognosis, and analysis of diseases has become a challenging task. The increasing diseases and its causes becomes a big question before humanity. Limited risk analysis, meticulous training process, and automated critical decision-making are some of the issues of cognitive computing. To overcome this issue, cognitive computing in healthcare works like a medical prodigy which anticipates the disease or illness of the human being and helps the doctors with technological facts to take the timely action. The main aim of this survey article is to explore the present and futuristic technological trends of cognitive computing in healthcare. In this work, different cognitive computing applications are reviewed, and the best application is recommended to the clinicians. Based on this recommendation, the clinicians are able to monitor and analyze the physical health of patients.This article presents the systematic literature on the different aspects of cognitive computing in healthcare. Nearly seven online databases such as SCOPUS, IEEE Xplore, Google Scholar, DBLP, Web of Science, Springer and PubMed were screened and the published articles related to cognitive computing in healthcare is collected from 2014 to 2021. In total, 75 articles were selected, examined and their pros and cons are analyzed. The analysis is done with respect to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines.The basic findings of this review article and their significance for theory and practice are mindmaps portraying the cognitive computing platforms, cognitive applications in healthcare, and use cases of cognitive computing in healthcare. A detailed discussion section highlighting the present issues, future research directions and recent applications of cognitive computing in healthcare. Accuracy analysis of different cognitive systems conclude that the Medical Sieve achieves 0.95 and Watson For Oncology (WFO) achieves 0.93 and hence proves to be the prominent computing systems for healthcare.Cognitive computing, an evolving technology in healthcare augments the clinical thought process and enable the doctors to make the right diagnosis and preserve the patient's health in good condition. These systems provides timely care, optimal and cost-effective treatment. This article provides an extensive survey of the importance of cognitive computing in the health sector by highlighting the platforms, techniques, tools, algorithms, applications, and use cases. This survey also explores about the works in the literature on present issues and proposes the future research directions of applying cognitive systems in healthcare.Copyright © 2023 Elsevier B.V. All rights reserved.