“Building a Global Healthcare Platform for 2040”
Introduction to Artificial Intelligence (AI)
Futurist Ray Kurzweil has predicted that computers will be as smart as humans by 2030. By 2045, he claims 'artificial intelligence' systems may be a billion times more powerful than our unaided 'human intelligence'. Are you prepared for what this means?
|In computer science, an ideal Artificial intelligence (AI) system is designed to mimic cognitive functions that humans associate with other human minds, such as “analyzing”, "learning" and "problem solving". Cognitive computers are self-learning artificial intelligence (AI) systems that can find patterns in massive collections of unstructured data and turn it into a presentable form for many others to use. For more detail, see Wikipedia.|
The promise of Artificial Intelligence (AI) has always been just beyond the horizon, not quite realistic yet still visible to our imagination through movies and literature. At its inception, AI was initially deployed for highly selective defense or space exploration applications. However, over time it has steadily advanced and has begun to be utilized in many other industries, such as healthcare and manufacturing.
Artificial Intelligence (AI) and Data-Driven Medicine
Artificial Intelligence (AI) and data-driven medicine are the next frontier in the healthcare revolution. Electronic Health Record (EHR) systems have been widely adopted by all major healthcare institutions across the US over the past decade. Now state and local Health Information Exchanges (HIE) networks are being deployed to allow access to data in the EHR systems by healthcare providers whenever or wherever it's needed.
In the meantime, consumers have been gradually starting to use Personal Health Record (PHR) systems that contain their patient data from the various EHR systems of healthcare institutions where they have been treated. Now we are seeing the growing use of other healthcare technologies that are also gathering and generating even more personal health data, e.g. wearable and implantable devices, genomic information systems and biorepositories, clinical imaging systems, and more.
It turns out that Medical data is the essential part of today's comprehensive healthcare systems. However, processing and analyzing the massive quantity of data now being generated by the wide range of converging health information technologies is almost too much to handle. It is an area the healthcare industry is struggling to come to grips with as it turns more and more to use of Artificial Intelligence (AI) as the means to gain control of the growing mountain of health related data.
|Roughly every three years, the amount of medical data on the planet doubles in size. By 2020, it is expected to double every 73 days.|
It is time to begin focusing more proactively on the design and development of a 'global healthcare platform for 2040' built on artificial intelligence (AI) technologies.
Artificial Intelligence (AI) in Healthcare
Analysts predict a tenfold growth of the use of artificial intelligence in healthcare in the next five years, for everything from cancer diagnosis to diet tips. According to Frost and Sullivan, healthcare providers will spend $6 billion per year on artificial intelligence tools by 2021. Google, IBM and Microsoft are all investing heavily in healthcare and analysts predict 30 percent of providers will run cognitive analytics on patient data by 2018. See Artificial Intelligence: There's Still Hope for the Human Race
Early types of these type of cognitive systems built on artificial intelligence (AI) technologies have already started entering the market. These include 'smart' triage systems that check patients’ symptoms against massive health data warehouses, then advise patients and providers what they should do next. Artificial Intelligence (AI) systems are also being used to help consumers when buying health insurance, to monitor biometric data from personal fitness trackers, analyzing genomic data to predict and potential life-threatening diseases, and much more.
Artificial Intelligence (AI) is advancing rapidly and is in the process of transforming the face of healthcare. Just a few of the many areas in which AI is being used to affect practice management and healthcare services include Diagnosis and Treatment, Disease Management, Personal Health & Wellness, Utilization Management & Reimbursement. Read 5 Ways AI is Changing Healthcare.
Other areas where AI technology and data-driven systems can be designed, developed, and used to improve healthcare include:
Examining and analyzing genomic data on hundreds of millions of patients.
Building systems that gradually teach themselves to become more accurate in its diagnosis.
Improving the speed and accuracy of diagnosis for genetic diseases.
Unlocking the possibility of personalized preventive and medical treatment plans.
Regularly monitor patients’ biometric data to see they are complying with their treatment plans.
Helping healthcare providers deliver better low-cost, evidence-driven care to consumers.
Helping consumers to avoid costly visits to doctor offices and hospitals.
Giving everyone in the world the equivalent of a doctor in their pocket – or smartphone.
By 2040, a space-based global artificial intelligence (AI) network
of satellites will be in place that will monitor and help provide
healthcare to people on Earth and in colonies across our solar
system on the Moon, Mars, and other locations. The system will be
linked to massive global health data warehouses storing data from
a wide range of health IT systems, e.g. Electronic Health Record
(EHR) systems, Personal Health Records (PHR), Health Information
Exchange (HIE) networks, wearable fitness trackers, implantable
medical devices, clinical imaging systems, genomic databases and
biorepositories, surgical robots, health research knowledgebases and more.|
The space-based global AI system will monitor and analyze the health data gathered on all humans in real-time, detecting potential individual and public health issues. The global AI system will detect problems, diagnose them, send alerts to patients and their healthcare providers, diagnose the problems and recommend treatment plans to resolve the healthcare issue. The system will also be interfaced to pharmacies, laboratories, health insurers, public health agencies, and other institutions as needed. The system will also be able to monitor a patient's progress, as well as adherence to recommended treatment plans. It will also seek to anticipate potential healthcare issues and provide preventive health and predictive health information tailored to each human.
Current News & Activities
The following are a few selected articles you might want to read to get a better handle on the latest news about current activities related to Artificial Intelligence (AI) in healthcare:
65+ Artificial Intelligence Startups In Healthcare - CB Insights From 'Virtual Nurses' to drug discovery, this article identifies more than 65 Artificial Intelligence (AI) Startups in Healthcare as of 2016.
Top-5 Artificial Intelligence (AI) Companies in Healthcare – 2016 There are quite a few artificial intelligence (AI) companies in healthcare already. CB Insights recently identified 65 of them at various stages of funding. The five AI companies on that list which have raised $40 million or more are described in this article by Nanalyze.
A new day is coming in healthcare, where AI will help diagnose and treat patients In 2013, Jeopardy! fans were blown away as IBM’s supercomputer WATSON wiped the floor with longtime champion Ken Jennings. Now Watson Health AI is being used in 16 cancer institutes across the country, helping to diagnose and treat patients. Meanwhile, Google has launched DeepMind Health to create innovative new apps for healthcare professionals alerting them to patient emergencies and the risk of complications when considering possible treatment options.
The following are some of the key issues that need to be addressed as we continue moving forward with the design, development, and use of AI technologies and data-drive healthcare information systems:
Privacy & Security – This is always a key issue. When AI systems are turned loose to monitor all health information systems gathering data on all facets of your personal health, concerns about who has access to the data and who it is being shared with are just a few of the issues that must be adequately addressed upfront.
Jobs - The Bank of England has predicted that intelligent machines might take over 80 million American and 15 million British jobs, respectively over the next 10 to 20 years. The healthcare industry will not be immune to this change.
Legal Issues - One of the most important points of interest that needs to be hammered out first is the legality of these machines. When a doctor's gross negligence leads to a misdiagnoses and patient harm, the fault is placed squarely on the shoulders of the offending physician. But what happens when a similar situation befalls an AI system? If such a program were to misdiagnose a patient, who's to blame?
Open Source - Many new 'open source' tools are arriving that can now run on affordable hardware and allow individuals and small organizations to perform prodigious data crunching and predictive tasks. Read about H2O, OpenAI, and other machine learning and AI tools being used in healthcare at Open Health News. Also, check out the growing List of AI Projects on Wikipedia.
|Regenstrief Institute and Indiana University School of Informatics & Computing, recently examined open source algorithms and machine learning tools in public health reporting: The tools bested human reviewers in detecting cancer using pathology reports and did so faster than people. Indeed, more and more healthcare systems on the cutting edge are looking at ways to harness the power of AI, cognitive computing and machine learning. See Artificial intelligence and cognitive computing - Healthcare IT News|
Recommended Next Steps
Artificial Intelligence (AI) systems today can learn in ways society once thought impossible, which has major implications for multiple industries – especially the healthcare industry. It is now time to begin focusing more proactively on a public-private sector collaboration to design and develop a 'global healthcare platform for 2040' built on artificial intelligence (AI) technologies. It's time to begin designing Health 4.0
Many countries are beginning to support the idea of having a global healthcare network of data centers coupled with a state-of-the-art AI technology platform that will allow sort through all the data, standardize it, and put it into a form that is useful and easily understood by patients, healthcare providers, healthcare insurers, researchers, and other individuals and organizations.
Any such global effort should keep in mind the key management strategies for success in the 21st century – Collaboration, Open Solutions, and continuous Innovation (COSI). Building such a global solution will require a massive global public-private sector partnership. Think of all the components that will need to converge to compose such a global solution – e.g. healthcare technologies, research, knowledge, organizations, and more.
One final note, advances in AI and technology are helping create a futuristic human-to-machine and machine-to-human interaction that can best be described as an 'Invisible' User Interface (IUI) of the future that simply works non-stop in the background to monitor and improve health for everyone. It will just be there – serving mankind.
Systems & Projects