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How the COVID-19 pandemic is fast-tracking AI health innovation

The COVID-19 outbreak has reminded the world that there’s a lot of truth in the old saying that necessity is the mother of invention. As businesses, schools, churches and other organizations have closed down to stem the spread of the virus, people quickly found ways to connect and interact with each other virtually. An accelerated outcome of the pandemic has been the decentralization of healthcare, which has allowed for real-time decision making around diagnosis and treatment.

Fortunately, digital technologies such as AI, machine learning and IoT are helping solve some of the most critical healthcare problems during these trying times. For example, keeping patient information safe while connecting several devices urgently during a pandemic requires an interconnected, secure digital ecosystem on the backend. In many cases, the tools required for these virtual interconnected interactions already exist, but adoption might be slowed because of policies and regulations.

For example, HIPAA rules in the U.S. don’t allow for the electronic exchange of patient data, which has limited providers’ ability to offer innovative telehealth services through FaceTime, Zoom or Skype. However, the coronavirus pandemic spurred the U.S. government to remove HIPAA penalties for telehealth out of necessity. In another sign of the times, many large insurers recently expanded coverage to include telemedicine.

Falling barriers are speeding up AI emergency help

Technology advancements are proving that health-oriented IoT devices are becoming more connected and data-driven. Though it may be hard to imagine what value a connected watch may have to a patient’s overall health, the digital platforms where these devices interconnect are becoming essential hubs of collaboration and innovation with their own inherent value.

Stanford University is hoping to turn wearables such as the Apple Watch and Fitbit’s health-tracking bands into the latest weapon in the fight against coronavirus. Recently, Stanford Medicine’s Healthcare Innovation Lab launched the Coronavirus Wearables Study to determine whether wearables can be used to detect if someone has COVID-19 before they start showing any symptoms. The idea is to gather data from the wearables to create algorithms that can detect and warn users for physiological changes when coming down with an infection.

In the past, inadequate compute power and lack of sufficient training data have impeded advances in AI. However, high-performance computing with interconnected supercomputers have essentially addressed the first challenge. The world’s fastest computer, IBM’s Summit supercomputer, can do 200 quadrillion calculations per second. To match what Summit can do in one second, 6.3 billion people would have to make a calculation at the same time, every second, for an entire year.

As for the second challenge, barriers to data sharing are being swept away as governments around the world race to find treatment options. For example, the entire genetic makeup of the virus was published online within days; lists of COVID-19 open datasets and resources have been published by the United Nations, the White House and Open Data Watch; local governments are pressing private labs to share data; and the European Data Protection Supervisor announced that data-sharing about the virus is acceptable.

IBM’s Summit is now being connected with other supercomputers to speed up COVID-19 research to find viable treatments, a process that would normally take up to 10 to 15 years to bring to market. Here are some other ways AI and IoT are helping during the pandemic:

  • Infectious disease surveillance spotted the outbreak nine days before WHO released a statement.
  • AI paired with sensors is helping to detect infections in travelers and high-risk populations.
  • Automated image analysis is speeding up diagnosis.
  • Machine learning is identifying patients with the highest risk of complications to prioritize care for the most vulnerable.
  • Digital assistants are accelerating medical transcription by recording doctor notes and automatically filling out electronic health records.
  • Drones and robots are being used to minimize exposure for healthcare workers on the front lines for everything from delivering food and medical supplies to disinfecting public areas to checking and treating patients remotely.

No looking back

Though the COVID-19 pandemic has helped to smooth the path for advances like these, it may have also moved the clock forward permanently in many ways. When things return to normal, providers, physicians and researchers will be more likely to share information and openly collaborate via virtual platforms, and patients will demand better access to telemedicine. In addition, communities that were hard hit will implement plans and tools to be better prepared in the future.

As a case in point, Wuhan, China opened a Smart Field Hospital that can serve up to 20,000 patients if regular hospitals in the region are overburdened by a resurgence in cases. All services in the hospital are carried out by robots and other IoT devices, such as smart bracelets and rings.

Moving forward on AI health innovation

Outside of the current emergency, other trends are also moving the needle forward, such as a rapidly aging and increasingly urban global population as well as emerging advances in 5G, IoT and the edge. Moreover, new approaches that address data sharing hurdles such as data privacy, security, compliance and interoperability are beginning to surface. These include anonymized aggregated datasets and data trusts, which include personal data stores, data collaboratives and trusted industry data exchanges.

The U.S. also recently issued new data interoperability rules aimed at standardizing data formats for easier data portability, and Apple has already jumped on board with a phone app for medical records. Unsurprisingly, the outlook for AI in the health market is bright; MarketsandMarkets projects it will reach $36.15 billion by 2025, growing at a 50.2% compound annual growth rate from 2018 to 2025. Some of the most promising use cases include:

  • Wellness and remote health monitoring.
  • Tracking outbreaks, disease surveillance and decision support for intervention.
  • Prioritizing cases for care, diagnosis and disease management assistance.
  • Genome sequencing, research and drug discovery.
  • Personalized genetics and care.
  • Chatbots and robotic assistants for providers, patients and the elderly.
  • Telemedicine and remote care and surgery.
  • Automation of administrative tasks, claims processing and fraud detection.
  • Restoring motor functions to the disabled with brain-computer interfaces.

Navigating the new world

The world was changing rapidly even before COVID-19, but the outbreak ushered in unprecedented collaboration and data sharing across digital ecosystems of government, industry, academia and citizens that has never been seen before. Facing a common challenge is bringing together people from across borders and from different sectors, such as healthcare working shoulder to shoulder with technology and government in the race to keep us all safe. AI has been helping to extend human capabilities to address these challenges faster and more efficiently, which will carry the world into the future of health.

All IoT Agenda network contributors are responsible for the content and accuracy of their posts. Opinions are of the writers and do not necessarily convey the thoughts of IoT Agenda.

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