Telecare medical information system (TMIS) is used to connect patients and doctors who are at a different location from each other. The authentication of the user and system is very crucial as the medical data of the user is stored on the server. Many systems have been developed in order to achieve this goal. We show some vulnerabilities of existing systems in this paper. We then propose a secure authentication mechanism to achieve the same goal. Machine learning and the nonce-based system is used for authentication of the entity and to prove the freshness of transmitted messages. Smart card blocking mechanisms have been included in each phase of the proposed system to prevent unauthorized access of data. The proposed system has been evaluated formally with the AVISPA tool. Then the proposed model has also been checked against different attacks and evaluated for different functionalities. We provide relative analysis with some recently proposed models and show our proposed system is relatively more efficient and secure.

远程医疗信息系统 (TMIS) 用于连接彼此位于不同位置的患者和医生。由于用户的医疗数据存储在服务器上，因此用户和系统的身份验证非常重要。为了实现这一目标，已经开发了许多系统。我们在本文中展示了现有系统的一些漏洞。然后我们提出了一种安全的身份验证机制来实现相同的目标。机器学习和基于随机数的系统用于对实体进行身份验证并证明传输消息的新鲜度。建议系统的每个阶段都包含智能卡阻止机制，以防止未经授权的数据访问。已使用 AVISPA 工具对提议的系统进行了正式评估。然后，还针对不同的攻击检查了所提出的模型并针对不同的功能进行了评估。我们提供了一些最近提出的模型的相关分析，并表明我们提出的系统相对更有效和安全。