We are facing a global healthcare crisis today as the healthcare cost is ever climbing, but with the aging population, government fiscal revenue is ever dropping. To create a more efficient and effective healthcare system, three technical challenges immediately present themselves: healthcare access, healthcare equity, and healthcare efficiency. An autonomous mobile clinic solves the healthcare access problem by bringing healthcare services to the patient by the order of the patient's fingertips. Nevertheless, to enable a universal autonomous mobile clinic network, a three-stage technical roadmap needs to be achieved: In stage one, we focus on solving the inequity challenge in the existing healthcare system by combining autonomous mobility and telemedicine. In stage two, we develop an AI doctor for primary care, which we foster from infancy to adulthood with clean healthcare data. With the AI doctor, we can solve the inefficiency problem. In stage three, after we have proven that the autonomous mobile clinic network can truly solve the target clinical use cases, we shall open up the platform for all medical verticals, thus enabling universal healthcare through this whole new system.

Dr. Shaoshan Liu is CEO and founder of PerceptIn, an intelligent robotics company. Although the world has witnessed tremendous economic growth and technological advancements in the past few decades, today there are still over 600 million people living in extreme poverty. Most of these people live in the least developed countries (LDCs), and while regular visits to our family doctors have become a routine in our daily lives, people who live in LDCs have very limited or even no access to healthcare. When we examine the details of healthcare expenditure data, the numbers are staggering: Developed countries (e.g., the Organization for Economic Co-operation and Development, or OECD countries) such as the U.S. spend roughly 10% of their GDP on healthcare, yet many LDCs don't even have 5% of their GDP to spare on healthcare. Realizing the seriousness of this problem, the United Nations Sustainable Development Goal 3 (SDG 3) has declared a universal health goal to ensure healthy lives and promote well-being for all by 2030.

Access to healthcare remains a pressing concern globally, especially among minority communities. The inherent societal bias has been a significant concern across the healthcare spectrum, especially in the wake of growing economic and social disparity. With the increasing adoption of AI technologies in different areas, there has been rising hope that its adoption in healthcare will help improve on existing medical technology, personalised medicine and provide reprieve and equity of access to the underserved and socially disadvantaged communities. However, the adoption of AI in healthcare must overcome critical challenges to ensure that AI technologies do not amplify the existing biases, which would render such a promoter of healthcare access inequality.

In a country such as India that has a low doctor-patient ratio, Artificial Intelligence (AI) can enable greater access to expert care from anywhere, with telehealth and robotics applied across inpatient and outpatient environments. Experts says AI will bolster the role of healthcare by assisting in screening, diagnosis, and treatment of diseases thereby improving quality of life and reducing the cost burden for patients. "India has a tremendous opportunity to lead human-centric applications and democratise AI for the world backed by high skilled talent, technology, vast data availability, and the potential for population-scale AI adoption," says Vice-president and managing director of Sales, Marketing and Communications Group, Intel India. Intel has been focusing its efforts towards accelerating AI innovation to deliver transformative healthcare solutions and democratise healthcare access and delivery in India. The company's portfolio of compute, memory, storage, and networking technologies powers some of the most exciting healthcare and life sciences applications.

In a country such as India that has a low doctor-patient ratio, Artificial Intelligence (AI) can enable greater access to expert care from anywhere, with telehealth and robotics applied across inpatient and outpatient environments. Experts says AI will bolster the role of healthcare by assisting in screening, diagnosis, and treatment of diseases thereby improving quality of life and reducing the cost burden for patients. "India has a tremendous opportunity to lead human-centric applications and democratise AI for the world backed by high skilled talent, technology, vast data availability, and the potential for population-scale AI adoption," says Prakash Mallya, vice-president and managing director of Sales, Marketing and Communications Group, Intel India. Intel has been focusing its efforts towards accelerating AI innovation to deliver transformative healthcare solutions and democratise healthcare access and delivery in India. The company's portfolio of compute, memory, storage, and networking technologies powers some of the most exciting healthcare and life sciences applications. The cloud-based AI solution Netra.AI is the latest example of the impact and innovation that can be made possible with Intel technology.

Justin Boutilier uses optimization and machine learning to improve healthcare access, delivery and quality, particularly in low- and middle-income settings. As a second-year PhD student at the University of Toronto, Justin Boutilier spent four weeks in Dhaka, Bangladesh, investigating ways to curb ambulance response times in the bustling capital of a developing country. He quickly got a firsthand look at the scope of the challenge: The roughly 10-mile trip from his hotel to meetings in the city took about three hours. "You could walk faster," he says, "but there's no sidewalk, so it's kind of dangerous." Boutilier, who has joined the Department of Industrial and Systems Engineering at the University of Wisconsin-Madison as an assistant professor, uses optimization and machine learning to improve healthcare access, delivery and quality, particularly in low- and middle-income settings.