Robots help patients get drugs on time: AI Healthcare's Catalia Health receives $2.5 million in financing

Mawi developer Catalia Health, an artificial intelligence patient interaction robot, received a new round of $2.5 million in financing, led by Khosla Ventures, NewGen Capital and Macnica Ventures, as well as existing investors Q Venture Partners Limited, InnoLinks Ventures and others. After the round of angel round financing, the company's total funds reached 3.75 million US dollars. The company will use the funds to establish and deploy a three-dimension nursing management system, and plans to launch the first two in this summer.

机器人帮助患者按时用药:AI医疗公司Catalia Health获250万美元融资

Ensuring that patients follow a medication regimen is critical to helping them treat their symptoms. In patients with chronic conditions, continuous medication is very important, and older patients may need more involvement to help them treat chronic diseases. San Francisco-based Catalia Health developed Mabu, a personal medical assistant robot to solve these problems. Founded in the United States in 2014, Catalia Health focuses on patient behavior research and services to help hospitals and care providers better serve patients by studying individual psychology, behavior, and habits. Mabu can not only help patients with chronic diseases, but also collect data for health care providers.

机器人帮助患者按时用药:AI医疗公司Catalia Health获250万美元融资

Mabu is a humanoid tablet that uses AI technology to provide medication compliance by monitoring the time and manner in which patients take medication. The system contains different algorithmic inputs that can be accessed by patients in the patient's home. Its specific behavior and preferences. Cory Kidd, the founder of the company, said that the core of his work is to understand the challenges faced by patients in specific situations, and then build AI algorithms and content based on this. Catalia Health customizes conversations with the person by establishing patient models, some of which are based on knowledge of medical staff, but primarily on patient psychology. For example, Mabu may initially tell the patient a joke, and its algorithm will further read the patient's emotional response to determine if the patient likes the joke.

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