The Covid-19 research challenge, also hosted on Kaggle, aims to provide a broad range of insights about the pandemic, including its natural history, transmission data and diagnostic criteria for the virus, and lessons from previous epidemiological studies to help global health organizations stay informed and make data-driven decisions. The challenge was released on March 16. Within five days it had already garnered more than 500,000 views and been downloaded more than 18,000 times.
Keep Reading
Early in the outbreak in China, Alibaba released that AI algorithm trained on more than 5,000 confirmed coronavirus cases. Using CT scans, it can diagnose patients in 20 to 30 seconds. It can also analyze the scans of diagnosed patients and quickly assess health declines or progress, based on signs like white mass in the lungs. Alibaba opened its cloud-based AI platform to medical professionals around the world, working with local partners on anonymous data for deployment, including modules for epidemic prediction, CT Image analytics, and genome sequencing for coronavirus.
With the amount of medical data in the world now estimated to double every couple of months or so, health care was ripe for AI—even before the virus struck. A 2019 study covering 19 countries’ artificial intelligence health care markets estimated a 41.7 percent compound annual growth rate, from $1.3 billion in 2018 to $13 billion in 2025, in six major growth areas: hospital workflow, wearables, medical imaging and diagnosis, therapy planning, virtual assistants, and, lastly but most significantly, drug discovery. Covid-19 will accelerate those trends rapidly.
Deep learning—the capability to process massive, multi-model data at high speeds—presents one of the most far reaching opportunities for AI. Deep neural networks, a subtype of AI, have already been used to produce accurate and rapid algorithmic interpretation of medical scans, pathology slides, eye exams, and colonoscopies. I see a clear roadmap of how AI, accelerated by the pandemic, will be infused into health care.
The potential goes beyond diagnosis and treatment. Getting appointments, paying insurance bills, and other processes should be much less painful. AI combined with robotic process automation can analyze workflows and optimize processes to deliver significantly more efficient medical systems, improve hospital procedures, and streamline insurance fulfillment. To address the pandemic, AI could automate and accelerate pre-diagnostic inputs by crunching texts, languages, and numbers at machine-level quantity and precision.
With sufficient data as a foundation, AI can also establish health data benchmarks for individuals and for populations. From there, it’s possible to detect variations from the baseline. That, in turn, positions us to identify potential pandemics early. It’s not easy. Systems need to be connected so that early alert and response mechanisms can be truly effective. That appeared to be a shortcoming in the early days of the coronavirus outbreak.
There are already huge opportunities for using AI models and algorithms for new drug discovery and medical breakthroughs in genomic sequencing, stem cells, Crispr, and more. In today’s pharmaceutical world, there is a hefty price tag to developing a treatment. A huge part of this cost is eaten up by the money and time spent on unsuccessful trials. But with AI, scientists can use machine learning to model thousands of variables and how their compounded effect may influence the responses of human cells.
These technologies are already being used in the hunt for a Covid-19 vaccine and other therapies. Insilico Medicine, a Hong Kong–based AI company specializing in drug discovery, was among the first companies to react to Covid-19. The company used its generative chemistry AI platform to design new molecules to target the main viral protein responsible for replication. It published the molecules on February 5. AI and machine learning are ushering in an era of faster and cheaper cures for mankind. Drug discovery and the pharmaceutical industry as a whole will be revolutionized.
Early one winter morning in the year 2035, I wake up and notice a bit of a sore throat. I get up and walk to the bathroom. While I brush my teeth, an infrared sensor in the bathroom mirror takes my temperature. A minute after I finish brushing my teeth, I receive an alert from my personal AI physician assistant showing some abnormal measurements from my saliva sample and that I am also running a low fever. The AI PA further suggests that I take a fingertip needle touch blood test. While the coffee is brewing, the PA returns with the analysis that I might be coming down with the flu, one of the two types around this season. My PA suggests two video call time slots with my family doctor, should I feel the need to consult her. She will have all the details of my symptoms when I make the call. She prescribes a decongestant and paracetamol, which is delivered to my door by drone.
