Healthcare delivery tomorrow will look much different than today for a variety of reasons. Consumer expectations, the emergence of nontraditional players, and a move to value-based care are among the driving forces. Yet nearly all advancements ride on the backbone of technology and the ability to harness a massive quantity of data now being produced. This June, HealthLeaders convened a select group of health system executive thought leaders to discuss the topic, "Healthcare System of the Future." In his keynote address to CEOs, CFOs, CMOs, and CNOs, as well as innovation and revenue cycle executives, John Halamka, MD, MS, president of the Mayo Clinic Platform, discussed the technology stepping stones that will pave the road forward.
Tinder users have known for a while that the price you pay for the dating app's premium service, Tinder Plus, might not be the same amount the people you're swiping are shelling out. Tinder has already settled an age discrimination lawsuit in California, which saw users over 29 in the state -- who, like all U.S. users, had been paying double what younger people were for the subscription -- eligible for part of a settlement totalling $23 million. Now the Australian consumer organisation Choice has filed an official complaint with the national consumer commission, the ACCC, after conducting a mystery-shopper survey that found prices for a one-month subscription to Tinder Plus ranged from AUD$6.99 to more than AUD$34, with no transparency upfront about the variation. Tinder Plus is the lowest tier of Tinder's premium subscription options, offering users extra features like unlimited swipes, the ability to undo left-swipes, and Super Likes and Boosts to help get your profile more attention. There's also Tinder Gold, which includes all the above as well as the ability to see who's already swiped right on you and Top Picks, and the new Platinum tier, which includes the ability to message people you haven't actually matched with yet.
Atomwise, which is using artificial intelligence for small molecule drug discovery, received a cash infusion of $123 million in an oversubscribed Series B financing. San Francisco-based Atomwise touts being the creator of the first convolutional neural networks, or visual imagery, using AI technology for drug discovery, a market estimated to reach $40 billion in value by 2027, according to Fior Markets research. To date, Atomwise has provided AI technology to more than 750 academic research collaborations addressing over 600 disease targets, Abraham Heifets, co-founder and CEO told Crunchbase News. B Capital Group and Sanabil Investments led the investment that also included existing investors DCVC, BV, Tencent, Y Combinator, Dolby Ventures, AME Cloud Ventures, as well as two undisclosed insurance companies. This brings the total amount of capital raised, since Atomwise's inception in 2012, to almost $175 million.
Steady advances in machine vision techniques such as convolutional neural networks powered by graphics processors and emerging technologies like neuromorphic silicon retina "event cameras" are creating a range of new predictive monitoring and maintenance use cases. We've reported on several, including using machine vision systems to help utilities monitor transmission lines and towers linked to wildfires in California. Now, AI software vendor Ignitarium and partner AVerMedia, an image capture and video transmission specialist, have expanded deployment an aircraft-based platform for detecting railway track obstructions. The AI-based visual "defect detection" platform incorporates Ignitarium's AI software implemented on Nvidia's edge AI platform used to automatically control onboard cameras. The system is designed to keep cameras focused on the track center during airborne inspections.
AI could also have a transformative effect on clinical decision-making through the utilisation of the huge levels of genomic, biomarker, phenotype, behavioural, biographical and clinical data that is generated across the health system. Bayer and Merck & Co provide a perfect example of this. They have developed an AI software system to support clinical decision-making of chronic thromboembolic pulmonary hypertension (CTEPH) – a rare form of pulmonary hypertension. The software helps differentiate patients from those suffering with similar symptoms that are actually a result of asthma and chronic obstructive pulmonary disease (COPD), and therefore diagnose CTEPH more reliably and efficiently. The CTEPH Pattern Recognition Artificial Intelligence obtained FDA Breakthrough Device Designation in December 2018.
In late February, a paper appeared in the journal Cell with encouraging news regarding one of the world's most persistent public health problems. Researchers at Massachusetts Institute of Technology and Harvard University had used artificial intelligence to identify a chemical compound with powerful antibiotic properties against some of the world's most drug-resistant strains of bacteria -- a welcome discovery in a world where 700,000 people die every year from drug-resistant infections. It was the first time an antibacterial compound had been identified this way. The researchers named it halicin, in honor of the computer HAL in the film 2001: Space Odyssey. While the global need for new antibiotics to treat drug-resistant infections is as pressing as it was at the start of the year, the world's attention has been diverted by the novel coronavirus pandemic, and the hunt for a vaccine that can halt Covid's spread.
An AI-controlled fighter jet will battle a US Air Force pilot in a simulated dogfight next week -- and you can watch the action online. The clash is the culmination of DARPA's AlphaDogfight competition, which the Pentagon's "mad science" wing launched to increase trust in AI-assisted combat. DARPA hopes this will raise support for using algorithms in simpler aerial operations, so pilots can focus on more challenging tasks, such as organizing teams of unmanned aircraft across the battlespace. The three-day event was scheduled to take place in-person in Las Vegas from August 18-20, but the COVID-19 pandemic led DARPA to move the event online. Before the teams take on the Air Force on August 20, the eight finalists will test their algorithms against five enemy AIs developed by Johns Hopkins Applied Physics Laboratory.
The White House and Defense Department on Monday announced a plan to accelerate the process by making a crucial new chunk of spectrum available to the wireless industry. The spectrum, which telecom companies will share with the Pentagon, aims to help wireless carriers offer 5G more broadly across the US. It also should generate billions of dollars for the US Treasury when auctioned off. The frequency is currently being used for high-power defense radar, but the DoD has determined that it can be freed up without affecting military systems. "It's a big deal," for the wireless industry, says Jason Leigh, an analyst at IDC who focuses on 5G.
San Diego Supercomputer Center makes high performance computing resources available to researchers via a "condo cluster" model. Many homebuyers have found that the most affordable path to homeownership leads to a condominium, in which the purchaser buys a piece of a much larger building. This same model is in play today in the high performance computing centers at many universities. Under this "condo cluster" model, faculty researchers buy a piece of a much larger HPC system. In a common scenario, researchers use equipment purchase funds from grants or other funding sources to buy compute nodes that are added to the cluster.
Machines have gotten smaller and more efficient over the years. However, the majority of these microscopic-scale machines have limited capabilities due to restrictive movements -- something which the scientists have been working to rectify. The most extensive use case of this kind of technology could be seen in the Healthcare sector. I have recently talked about the extended role of nanotechnology in the future of Healthcare. Taking inspiration from the Japanese art of Origami, researchers at the University of Michigan have taken this approach to create more agile micro machines to be used in diverse fields like medical equipment and infrastructure sensing.