An UPDATED version of this presentation is available at http://healthcybermap.org/KamelBoulos-CN-AI-Apr19.pdf How is AI actually empowering clinicians, augmenting telehealth, and transforming the world’s largest healthcare system (serving 1.4 billion people in China)? 智能医学

1. How is AI actually empowering clinicians,
augmenting telehealth, and transforming the
world’s largest healthcare system (serving 1.4
billion people in China)?
Prof. Maged N. Kamel Boulos, MBBCh, PhD, SMIEEE
♦ Increasing healthcare demands ♦ AI can help ♦ The healthcare AI industry in China (with examples)
♦ How can we accelerate digital/AI developments towards more efficient, accessible and preventive healthcare
智能医学
Reading between the lines of news media hype

2. China’s rapidly increasing healthcare demands
• China’s population is growing older.
By 2040, the country’s population over 65
will reach about 303 million (UN WPP).*
• Today, there are already 300 million people
in China suffering from chronic diseases**
and putting a heavy burden on the
country’s healthcare system.
• Doctors’ shortage: China has 1.8 practising
doctors per 1,000 citizens, compared to 2.6
for the USA and 4.3 for Sweden.
• China’s megacities and urban hospitals are
overcrowded, with a typical outpatient
department in Beijing seeing about 10,000
people*** every day! This is compounded by
the scarcity of (advanced) medical facilities in
rural areas, causing more people to flock to hospitals
in nearby cities.
^ https://data.oecd.org/healthres/doctors.htm
* https://chinapower.csis.org/aging-problem/
** http://en.people.cn/n3/2016/0811/c90000-9098949.html
*** https://www.technologyreview.com/s/610397/ai-could-alleviate-chinas-doctor-shortage/

3. AI can help!
• In its determination to offer accessible and affordable care for all, the Chinese government
is spearheading the development of digital health/care technologies, including artificial
intelligence (AI), as part of its Healthy China 2030 national strategy.
• AI can help us make sense of big data. With its 1.4 billion population, China sits on massive
goldmines of health/care data.
• In 2017, the city of Guangzhou in collaboration with ophthalmologists at Sun Yat-Sen
University launched the first AI clinic experiment in China to diagnose cataracts (subject
to further clinical trials), in response to the shortage of eye care specialists in China.
<< https://www.livescience.com/57696-artificial-
intelligence-cataract-diagnosis.html

4. The AI Doctor’s role is to gather medical history and come up with a diagnosis plan, which
can then be passed on to a specialist consultant via telemedicine. The miniature clinics, called
“One-Minute Clinics”, can connect patients with a clinician on Ping An Good Doctor’s in-house
medical team. The system also includes a smart medicine cabinet where patients can get
their medication after getting a diagnosis.
It includes upwards of 100 common medications.
AI can help!
• In another experiment, similar in many ways to the UK’s Babylon Health service
(https://www.babylonhealth.com/ and https://www.gpathand.nhs.uk/), Ping An Good Doctor introduced its
first commercially operational unmanned AI clinic in Wuzhen, China, in November 2018.
^ Clip from a 2018 BBC documentary entitled ‘Diagnosis On
Demand? The Computer Will See You Now’ (time position 00:55:35)
<< https://en.prnasia.com/releases/apac/the-first-unmanned-clinic-reveals-
itself-in-wuzhen-ping-an-good-doctor-uses-ai-technology-to-empower-a-
healthy-city-228380.shtml

5. • At least 131 Chinese
companies are
currently working on
applying AI in
healthcare
(2017 estimate by
Yiou Intelligence, a
Beijing-based
consultancy firm:
https://www.iyiou.com
/intelligence/reportPre
view?id=83017&&did=
561).
• By 2017, venture
capitalists had already
invested at least
CNY 18 billion in such businesses, according to Yiou.
• Other analysts (Bernstein) estimate that spending in China’s health tech industry will reach CNY 150
billion by 2020 (https://www.reuters.com/article/us-china-medtech-breakingviews/breakingviews-really-big-data-gives-china-medical-ai-edge-idUSKBN1K808W).
The healthcare AI industry in China
^ Really Big Data gives China medical AI edge (Reuters, 18 July 2018)

6. < 17 September 2018 at
http://www.openhealthnews.com/story/2018-09-
17/china-already-21st-century-fields-ai-healthcare-
and-quantum-computing
Cited by above news report:
• AI could alleviate China’s doctor shortage - Chinese doctors
and tech companies are developing tools to automate routine
medical tasks (21 March 2018)
https://www.technologyreview.com/s/610397/ai-could-
alleviate-chinas-doctor-shortage/
• AI ambulances and robot doctors: China seeks digital salve to
ease hospital strain (28 June 2018)
https://www.reuters.com/article/us-china-healthcare-tech/ai-
ambulances-and-robot-doctors-china-seeks-digital-salve-to-
ease-hospital-strain-idUSKBN1JO1VB
• China counts on AI to find a cure for its ailing health care
system (2 July 2018) https://www.scmp.com/tech/china-
tech/article/2153144/china-counts-ai-find-cure-its-ailing-
health-care-system
• China plans to dominate AI, with a vanguard of robotic doctors
like 'Biomind' (6 July 2018) https://www.latimes.com/world/la-
fg-china-ai-20180706-story.html
• China leading in healthcare technology, says Medix chief (6
September 2018) http://www.ejinsight.com/20180906-china-
leading-in-healthcare-technology-says-medix-chief/
• China's Infervision brings AI medical image analysis to 200th
hospital (12 September 2018)
https://www.dotmed.com/news/story/44345

7. According to a recent New York Times news report (31 January 2018),
advances in digital health/care including AI have been transformative for
China’s overworked doctors:
• In 2017, Alibaba’s health unit introduced AI software that can help
interpret CT scans and an AI medical lab to help doctors make
diagnoses.
• Also in 2017, Tencent unveiled Miying, a medical imaging program that
helps doctors detect early signs of cancer, in the southwestern region of
Guangxi. It is now used in nearly 100 hospitals across China.
• Tencent also invested in WeDoctor Group, which has opened its own
version of the ‘GP at hand’ component of UK Babylon Health in north-
western China. The service allows patients to video chat with doctors
and fill their prescriptions online.
• Yu Weihong, an ophthalmologist at Peking Union Medical College
Hospital, said she used to take long time to analyse a patient’s eyes by
scrutinising grainy images before discussing her findings with colleagues
and writing up a report. AI software currently being tested by the
hospital helps her do all that dramatically faster (in a minute).
The software has been developed by VoxelCloud, a start-up that raised
about USD $28.5 million from investors including Tencent. It does
automated medical image analysis, helping eye doctors screen patients
for diabetic retinopathy, the leading cause of blindness among China’s
working-age population. In 2017, Beijing announced an ambitious plan
for the country’s 110 million diabetics to undergo eye tests. But there
are just 20 eye doctors for every million people in China, a third of the
proportion in the US.
https://www.nytimes.com/2018/01/31/
technology/amazon-china-health-care-
ai.html

8. “Now, you don’t even need a minute” -- Yu Weihong, an ophthalmologist
at Peking Union Medical College Hospital, China
http://www.voxelcloud.io/

9. According to a recent New York Times news
report (31 January 2018) – Cont’d:
• In 2017, China’s search engine company Baidu scrapped its Internet healthcare service, which allowed patients to book
doctors appointments through an app, in a bid to focus solely on AI and machine learning/deep learning.
http://research.baidu.com/Blog/index-view?id=104
cf. Google
projects: https://deepmind.com/applied/deepmind-health/

10. • Yunfeng, the personal investment fund of
Alibaba’s founder Jack Ma, invested in a new
company, Yitu. The company is working with
Zhejiang Provincial People’s Hospital to
develop software that automates the
identification of early stages of lung cancer.
“In China, medical resources are very scarce
and unequally distributed so that the top
resources are concentrated in provincial
capitals. With this system, if used at hospitals
in rural cities, it will make the medical
experience much better,” according to Yitu.
China’s doctors have far less time and
resources than their counterparts in the US
and elsewhere, and Gong Xiangyang, the head
of the hospital’s radiology department,
likened the process to a factory, where
burnout and mistakes from overwork can
happen. “We have to deal with a vast amount
of medical images everyday,” he said. “So we
welcome technology if it can relieve the
pressure while boosting efficiency and
accuracy.”
According to a recent New York Times news
report (31 January 2018) – Cont’d:
http://www.yitutech.com/en/corebusiness/6.html

11. • In 2017, DXY released China’s first AI-based skin disease diagnosis system, in collaboration with the Second
Xiangya Hospital of the Central South University in Changsha, Hunan province, and Glority, an AI technology
company in Hangzhou, Zhejiang province.
• After undergoing testing and deep learning for a year, based on the data bank of China’s nationally reputed
Hospital for Skin Disease, the system is now able to diagnose 85 types of skin diseases with an overall accuracy
of 86%. Among 35 common skin diseases, the accuracy reaches >95%, according to DXY data.
• In April 2018, the system officially opened to doctors, who can upload photos of their patients’ skin lesions
through WeChat to the platform, and receive AI advice within seconds on diagnosis and treatment, as well as
other information related to the condition at hand.
• This system means a lot for the country. China has only 20,000 dermatologists, many of whom are in
cities rather than in rural areas, and in the eastern regions rather than the west. There are many
hospitals in remote areas that cannot afford a dedicated skin disease department.
___________________________________________________________________________
cf. VisualDX Aysa, a similar system developed in the US:
https://www.visualdx.com/in-the-news/visualdx-launches-aysa-for-consumers-to-check-skin-conditions-using-ai
According to Tech Wire Asia (15 June 2017) https://techwireasia.com/2017/06/hunan-based-hospital-developing-app-diagnose-skin-diseases-ai/
and China Daily (5 December 2018) http://www.chinadaily.com.cn/a/201812/05/WS5c072c33a310eff30328f1e9.html :
AI can help!

12. AI can help: Solving operational bottle-
necks, improving clinicians’ workflows and
maximising efficiencies in China’s hospitals
• Patient data are often stored in many disparate
systems and formats. For example, at Zhongshan
Hospital in Shanghai, a clinician used to spend days to
manually locate/request, extract and link (‘make sense
of’) all relevant patient information from 200
unstructured medical reports into one structured
format.
• The hospital then called on the AI expertise of Philips
China. By combining AI methods such as natural
language processing and machine learning with
clinical knowledge, it is now possible to collate and
make sense of all clinically relevant information about
the patient in one accessible dashboard, enabling
clinicians to spend less time capturing information
from unstructured reports and handwritten notes, less
time sitting in front of a screen trying to compile a
complete picture of the patient, and more time seeing
more patients and better serving them. ^ http://www.chinadaily.com.cn/a/201805/15/WS5afa2722a3103f6866ee8581.html
See also: http://www.chinadaily.com.cn/a/201812/01/WS5c0163baa310eff30328c226.html

13. AI can help: Augmenting telehealth/care
to counter congestion in city hospitals
• The widespread adoption of AI technologies in
China is going hand in hand with investments in
primary care facilities and Internet connectivity
in rural areas, making healthcare more equally
accessible and affordable for everyone, and
allowing people to enjoy a better quality of life
where they live without the need to travel to
big healthcare centres in nearby/provincial
cities.
• Smart telehealth/care: AI-powered telehealth
monitoring technology at home is helping the
frail and older people stay connected with
professional caregivers, ensuring they receive
timely care when needed. People with diabetes
or hypertension are also benefiting from similar
technologies that allow them to track and
manage their condition via clinically-validated
sensors and devices.
^ Research done at Xiamen University of Technology and Hunan
Provincial Key Laboratory of Network Investigational Technology:
J. Hu, X. Chen, Y. Wang, Y. Huang and X. Su, "Cloud-assisted home
health monitoring system," 2017 IEEE/ACIS 16th International
Conference on Computer and Information Science (ICIS), Wuhan, 2017,
pp. 899-903.
doi: 10.1109/ICIS.2017.7960120

14. AI can help: Lifestyle-related diseases
such as obesity and type 2 diabetes
• Overweight and obesity are a major health
concern in China, affecting about 1 in every 8
people in the country. They are a documented
leading risk factor of major non-communicable
diseases, including type 2 diabetes. China now has
the world’s largest and fastest growing diabetes
epidemic: the latest prevalence figures in China
are ~11% for diabetes and ~36% for prediabetes,
i.e., almost half of the nation is affected (Wang
et al., 2017 in JAMA 2017;317(24):2515-2523).
• Now imagine individuals at high risk of obesity
and diabetes being clinically monitored via a
smart telehealth/care service to receive
bespoke lifestyle coaching and feedback on
their smartphone.
• On a population (big data) level, analyses of collected data aggregates could inform public interventions
targeted at specific age groups or regions/cities. This is inline with the Chinese government’s ‘Healthy
China 2030’ strategy, in which the focus of the healthcare system is increasingly shifting from treatment to
prevention.
No more manual
estimation and logging of
diet and exercise = improved user
compliance and adherence
Smart
speaker
NIR spectroscopy
^ Kamel Boulos, 2017: A novel multi-disciplinary programme of research presented
during SYSU’s 2017 Int’l Scholars Forum in Guangzhou, focusing on intelligent IoT
applications in the domains of food and nutrition informatics (‘Internet of Food’) and
lifestyle informatics (fitness, sleep and lifestyle tracking). At the heart of the
proposed system is an intelligent, cloud-based Decision Support System (DSS) for
personalised lifestyle optimisation (offering detailed and continuously updated diet,
exercise and other lifestyle recommendations) that can be used by a layperson on
his/her own, and is carefully tailored per individual needs, age, comorbidity, etc.

15. How can China (and other countries) accelerate these digital/AI developments
towards more efficient, accessible and preventive healthcare?
• Building a robust and reliable (national) data ecosystem: The quality of AI is only as good as the
quality of data fed into it. The quantity and diversity of high quality data are also important for
machine learning/deep learning systems (‘the more you see, the better you learn and avoid
“narrow vision” and bias’). Shared data standards, interoperability of systems, and improved data
exchange (with top-notch security safeguards) are key to realising this data ecosystem. China’s
plan to establish three digital national databases by 2020 containing health information, health
profiles and medical records is a major step in this direction.
<< https://www.aiin.healthcare/topics/diagnostics/ai-tools-worse-
tested-data-outside-original-system and
https://doi.org/10.1371/journal.pmed.1002683
Deep Learning models trained to detect pneumonia from chest X-rays
performed worse when tested on X-rays from outside their original
hospital systems, suggesting AI tools should undergo a wide range of
testing before being used in clinical settings.

16. How can China (and other countries) accelerate these digital/AI developments
towards more efficient, accessible and preventive healthcare?
• Data-driven AI approaches must be combined with proven medical expertise
and a deep understanding of the clinical context: AI is only part of any
solution; it is never a complete solution by itself. All forms of AI-aided care must
be centred around the clinician and the patient, observing their needs and
preferences, and capitalising on the wealth of clinical and other relevant types
of evidence- and practice-based knowledge that are already available.
• Educate clinicians in AI and machine learning: In a 2018 NPJ Digital Medicine
article (available at https://www.nature.com/articles/s41746-018-0061-1),
Kolachalama and Garg argue that “educating the next generation of medical
professionals with the right (machine learning) techniques will enable them to
become part of this emerging revolution. Yet, the medical school curriculum as
well as the graduate medical education and other teaching programs within
academic hospitals across the United States and around the world have not yet
come to grips with educating students and trainees on this emerging
technology”.
• Ultimately, the goal should not be to replace clinicians, but to augment and
empower them in their daily work, strengthening their role in the delivery of
efficient and high-quality care—think of it as a ‘cognitive prothesis’ for
clinicians. AI should make healthcare more – not less – human.

17. How can China (and other countries) accelerate these digital/AI developments
towards more efficient, accessible and preventive healthcare?
• Develop, nurture and retain a strong local digital healthcare talent/workforce and industry* to work with
clinicians and patients on building and maintaining next-generation smart/AI-enabled (tele)health/care tools.
• Regulatory compliance (full approval and certification must always be sought prior to full-scale
deployment): In 2014, Alibaba announced a “future hospital” plan intended to make treatment more
efficient by allowing patients to consult with doctors online and order drugs via the Internet. But the service
was never properly validated or evaluated prior to full deployment. Two years later, Chinese regulators
stopped the sale of over-the-counter drugs on Tmall, Alibaba’s e-commerce Web site, and suspended a drug-
monitoring system that Alibaba had created.
• AI-driven clinical/health tools and interventions must be rigorously tested and evaluated against the
highest clinical and regulatory standards (‘software as a medical device’ or SaMD): Only with proper and
thorough clinical validation and evaluation can we ensure responsible, safe, reliable and effective use of AI.
Clinicians, as well as patients (where applicable), should also receive appropriate education regarding a tool’s
strengths and limitations before using it to prevent human errors/misuse of the tool.
• Policies and regulatory requirements should be
revisited and updated to match the pace of
development of new health/care technologies
and to properly deal with them in a timely manner.
http://eng.sfda.gov.cn/
* esp. in medical AI/machine learning and data science

18. << The US FDA recommends sensitivity,
specificity and odds ratio for clinical
validation of AI. Source:
https://www.fda.gov/downloads/medicalde
vices/deviceregulationandguidance/guidanc
edocuments/ucm524904.pdf
See also: Roundup of 12 healthcare
algorithms cleared by the (US) FDA
(November 2018). “As AI cements its role in
healthcare, more and more intelligent
software offerings are pursuing (US FDA)
510(k) and De Novo approvals.”
https://www.mobihealthnews.com/content/
roundup-12-healthcare-algorithms-cleared-
fda
Regulatory compliance –
Cont’d

19. How can China (and other countries) accelerate these digital/AI developments
towards more efficient, accessible and preventive healthcare?
• Close and continuing collaboration between the
academia/research communities and the health/care
industry (the country’s healthcare services and
hospitals, and digital health/care start-ups and
companies) is mandatory. The size of, and challenges
in, China’s healthcare system are simply too big for
any single player to tackle it alone.
The Chinese government is to be commended for
establishing in May 2018 the Chinese Intelligent
Medicine Association, a collaborative platform to
promote the exchange of ideas, and kick-start new
projects in intelligent medicine that integrate AI with
medical care to improve services across the country.
The Association will have specialist sub-
committees, e.g., a digestive endoscopy AI
sub-committee, etc.
http://www.chinadaily.com.cn/a/201805/07/
WS5aef9beea3105cdcf651c45a.html >>

20. Discover more AI in medicine and health/
care news, examples and insights at
https://plus.google.com/collection/40E-LE