The complexities in healthcare are responsible for the inefficiencies the industry has been grappling with for decades. It’s a sweeping problem, affecting virtually every sector as legacy technologies try to cope with the sheer size of the challenges it’s facing. While digital technology is making strides, one particular segment, Artificial Intelligence (AI), is turning hope and hype into real-world results.
Watson for Drug Discovery ranked all of the nearly 1,500 genes within the human genome for predicting which genes might be associated with ALS. This was accomplished in a matter of months. Barrow Neurological Institute, which carried out the research with IBM, went through the data and found eight of the top 10 ranked genes proved to be linked to the disease. If that wasn’t impressive enough, five never before linked genes associated with ALS were also found.
So what are some of the ways AI is disrupting healthcare, and which companies are finding solutions for this particular problem?
Many chronic health conditions require constant monitoring of patients. Monitoring is a labor and resource intensive process, whether it’s carried out on-premises at the hospital or remotely in the patient’s home.
Virta Health is addressing a particularly monitor intensive condition, diabetes. The company says it wants to reverse type 2 diabetes with a two pronged approach, with the first being individualized nutrition. The second step is using its technology and AI, enabling doctors to remotely monitor patients and receive real-time data analysis through a mobile app.
The company, which just launched in March, 2017, has already raised over $37 million in funding.
Imaging technology has come a long way from the blurry X-ray images of the past. However, even with today’s advanced MRI and CT scans, accurate diagnosis is a big problem. Two radiologists can reach different conclusions from the same image. What’s more alarming is, the same healthcare professional can also reach a different conclusion from the same image when it is shown at different times.
The application of AI in imaging has been welcomed with open arms, and Infervision has developed a solution in partnership with GE Healthcare, Cisco and NVidia to score images of lung cancer patients more accurately.
The platform uses Deep Learning and AI technologies to quickly duplicate top medical expertise and diagnose the images. To date, Infervision has processed roughly 100,000 CT scans and 100,000 x-rays.
Diagnostics is one segment in healthcare ripe for major disruption. The practice has many procedures that can be automated, which is what Babylon Health has managed to do with its technology.
Babylon Health has raised $85 million to create its platform. Using a combination of AI, video and text consultations, an automated triage service allows users to text their symptoms to the app. The AI then diagnoses the patient and makes real time recommendations.
The company has greater ambitions though. First, it wants to create a robot doctor that can triage, diagnose and even treat individuals over their phones, followed by machine-learning algorithms that will eventually calculate possible future illnesses by analyzing the health profile of individuals.
Healthcare organizations operate to perform optimally at all times. This, of course, is not always possible and mistakes often happen. Qventus was established to simplify healthcare operations for improving small day-to-day decisions with long term impact.
The company has developed an AI-based software platform to harness the power of data and identify problems before they take place. Based on the analysis, it makes accurate and immediate recommendations for hospital administrators so they can make informed decisions. This includes emergency departments, perioperative areas, patient safety and more.
There is no question the pharmaceutical industry is responsible for developing ground breaking drug therapies. The problem is the cost and time associated in introducing new drugs into the market place.
Atomwise wants to reduce both the time and cost by predicting potential drug cures using AI, supercomputers and a special algorithm to run through millions of molecular structures. The company recently proved the viability of its technology by finding two drugs for Ebola virus in less than one day, instead of months or years. It did so by launching a search for drugs that already exist, but could be redesigned to treat Ebola.
The possibilities are limitless. Alexander Levy, COO of Atomwise, put it best when he said, “Imagine how many people might survive the next pandemic because a technology like Atomwise exists. He goes on to say, “We can even consider hypothetical drugs that don’t even exist yet. Atomwise can look at weaknesses on those new viruses and rapidly identify hypothetical treatments to test.”
When it comes to finance, the numbers in healthcare are enormous. In the US alone, 2016 saw the country spending $3.4 trillion – that is not a typo, it is in the trillions. According to The Washington Post, it is slated to grow to $5.5 trillion by 2025. The cost of bringing a new drug to market is also expensive, typically taking 12 to 14 years and the average cost coming in anywhere from $2.5 to $2.9 billion.
Artificial Intelligence may not solve all that ails the healthcare industry, but it will make dramatic improvements in the way things get done in the short and long run.