Philips and Huawei: Just What the Doctor Ordered
Rapid disruption is happening in the healthcare space, with cloud, AI, and biosensors poised to form your personal health team. Find out what Philips and Huawei are doing to get you there.
In the fourth quarter of 2016, Huawei and Phillips signed an MoU, planning to deploy a cloud healthcare solution in China. Currently, the solution has already completed testing. Using cloud and machine learning technologies, this solution will sweep the healthcare industry in an unprecedented pace and scope, creating a new digital healthcare future.
Huawei and Phillips’ cooperation will mainly look at second-tier cities in China, aiming at providing high quality cloud healthcare services to communities lacking advanced healthcare solutions or professional doctors.
Compared with traditional doctors, cloud Artificial Intelligence (AI) can process large volumes of data more agilely and precisely. Phillips’ China Region Health Management Director Liang Jianqiu points out that cloud AI technologies are specially important for China second-tier cities because many doctors “do not necessarily possess diagnostic imaging skills such as nuclear magnetic resonance or CTs. If doctors diagnose thousands of image reports daily, it is easy for them to make a mistake.” On the other hand, AI can easily identify patterns from large volumes of data. For cancer and other serious diseases, the cloud terminal machine learning solution can more precisely determine how much a patient's disease has advanced.
Therefore, applying cloud AI technology to the healthcare domain will benefit individuals, doctors, and all of society.
Mobile technologies and applications will make self-service healthcare management a reality, promoting healthcare management from passive and scattered modes to active and real-time management modes. Liang Jianqiu said “people can use an APP and obtain objective data from the cognitive devices instead of a couple of words from other people.”
With the increasing popularity of active monitoring, early intervention, and even remote treatment and other personal healthcare management methods, patients can consult with professional medical personnel at any time to understand their health situation. For example, the ‘Life Records’ application’s data can record a person’s daily life habits and use wearable products to monitor the user’s health situation while giving feedback to the person’s doctor through data in real-time. Liang Jianqiu says that if a user’s heartbeat is abnormal, then “you can identify health problems that are difficult to detect by setting thresholds to send feedback to your doctor if there is abnormal data.”
Liang Jianqiu pointed out a relatively realistic view: “We have made breakthroughs in some emerging domains. Healthcare is gradually extending from hospitals to homes. Healthcare applications and Internet-connected devices’ applications are continuously becoming more common.” The concept of expanding healthcare services is of big significance. It means that patients’ treatments will no longer be limited to hospitals or doctor offices. The emergence of healthcare applications, sensors, smart terminals, and cloud computing means that “patients will have a healthcare team that provides them with 24/7 services.”
Wearable technology is still not popular, but it is just a matter of time. Liang Jianqiu said that “the American Food and Drug Administration is authenticating some wearable products, so they will finally become a reality.” In the future, bio-sensing technology will comprehensively report a person's health situation. At the same time, the development of machine learning helps people accurately predict disease development trends. For example, smart phones can use voice analysis technology, using the user’s voice to conduct analysis, identify pressure, heart diseases, or Alzheimer’s, among others. Wheelchairs can recognize Parkinson’s early symptoms through slight tremors in the hands and some devices can scan people’s bodies for tumors when they bathe.
Apart from this, Liang Jianqiu still believes that mastering the skills to use AI technology is not difficult for users: “The age of computers and mobile application users is on the rise, many 50 to 60-year-olds are already learning how to use WeChat and other social media platforms. They are quickly adapting to the development of new technology.” In this aspect, the younger generation will play a key role. For example, “they might think: ‘How is my father doing today?’ And they will actively understand their parents or grandparents’ health situation, so they will make sure that they can use these new technologies.”
Apps that record behavior and health monitoring sensors can ensure patient’s cooperate with their treatment plan by sending them reminders or alarms, increasing treatment efficiency.
Cloud AI technology can greatly reduce doctors repetitive work and bring benefits from two aspects. First of all, in terms of clinical treatment, doctors can let computers handle a portion of their work, such as disease diagnosis. Computers also observe abnormalities more accurately than humans. For example, a thrombus or bleeding can cause a stroke, and doctors must diagnose and treat within the first 45 minutes which are as valuable as gold, eliminating the thrombus as soon as the symptoms appear. Besides, manual scanning often takes hours and even days before identifying visible thrombus shadows. Using cloud AI technology can avoid this kind of situation.
Second, cloud AI technology can also assist doctors in increasing information sharing efficiency by quickly invoking large amounts of data to research a disease. Liang Jianqiu expressed that “doctors can record case data from a long period of time, being able to further understand the symptoms from different diseases and identify efficient treatment.”
Cloud AI and analyzing large volumes of data can improve people’s health by identifying potential epidemics, real-time monitoring, and studying the relationship between rare diseases and certain groups of people and areas. Compared to human-made analysis, cloud AI technology is definitely better.
For China, Liang Jianqiu believes that technical solutions have three problems: “The first problem is having an aging society. As people’s life spans become longer, people rely more on healthcare resources. Second, the costs of monitoring chronic diseases are continuously increasing, posing a heavy burden on society. There is hope that this problem can be fixed using technical solutions. And the final problem is solving the problem of uneven distribution of healthcare resources.”
Phillips and Huawei’s joint solution will cut costs, improve diagnosis and treatment efficiency, and quickly and accurately create a fair healthcare environment. Liang Jianqiu said: “Our cooperation with Huawei built a cloud platform, enabled IoT connection, and develop a solution. We are already testing these solutions on the cloud platform provided by Huawei, and we have obtained positive results. In the future, Phillips and Huawei will promote the healthcare solutions market hand in hand.”