RSNA – The Health Care Blog

RSNA 2019 AI Round-Up

Dec 10, 2019

By HUGH HARVEY, MBBS and SHAH ISLAM, MBBS

AI in medical imaging entered the consciousness of radiologists just a few years ago, notably peaking in 2016 when Geoffrey Hinton declared radiologists’ time was up, swiftly followed by the first AI startups booking exhibiting booths at RSNA. Three years on, the sheer number and scale of AI-focussed offerings has gathered significant pace, so much so that this year a decision was made by the RSNA organising committee to move the ever-growing AI showcase to a new space located in the lower level of the North Hall. In some ways it made sense to offer a larger, dedicated show hall to this expanding field, and in others, not so much. With so many startups, wiggle room for booths was always going to be an issue, however integration of AI into the workflow was supposed to be a key theme this year, made distinctly futile by this purposeful and needless segregation.

By moving the location, the show hall for AI startups was made more difficult to find, with many vendors verbalising how their natural booth footfall was not as substantial as last year when AI was upstairs next to the big-boy OEM players. One witty critic quipped that the only way to find it was to ‘follow the smell of burning VC money, down to the basement’. Indeed, at a conference where the average step count for the week can easily hit 30 miles or over, adding in an extra few minutes walk may well have put some of the less fleet-of-foot off. Several startup CEOs told us that the clientele arriving at their booths were the dedicated few, firming up existing deals, rather than new potential customers seeking a glimpse of a utopian future. At a time when startups are desperate for traction, this could have a disastrous knock-on effect on this as-yet nascent industry.

It wasn’t just the added distance that caused concern, however. By placing the entire startup ecosystem in an underground bunker there was an overwhelming feeling that the RSNA conference had somehow buried the AI startups alive in an open grave. There were certainly a couple of tombstones on the show floor — wide open gaps where larger booths should have been, scaled back by companies double-checking their diminishing VC-funded runway. Zombie copycat booths from South Korea and China had also appeared, and to top it off, the very first booth you came across was none other than Deep Radiology, a company so ineptly marketed and indescribably mysterious, that entering the show hall felt like you’d entered some sort of twilight zone for AI, rather than the sparky, buzzing and upbeat showcase it was last year. It should now be clear to everyone who attended that Gartner’s hype curve has well and truly been swung, and we are swiftly heading into deep disillusionment.

HIMSS12 Takeaway: Follow the Money

Nov 1, 2018

By John Moore

Last week we attended the big healthcare IT confab HIMSS in that grand city of sin, Las Vegas. While many spoke of how HIMSS hit an all time record of over 37K attendees (an impressive number), HIMSS is still dwarfed by what is arguably the largest US-based healthcare trade show, RSNA, which had a 2011 attendance of just over 57K, (roughly 54% greater than HIMSS). Why such a radical difference you ask? As one colleague put it:

RSNA is where providers come to make money and HIMSS is where they go to lose money.

While that may be the case today, it is unlikely to be so in the future. The healthcare industry is undergoing a massive transformation that will likely take a decade to complete as we transition from a reimbursement model largely based on fee for service to one based on outcomes. Under this new model, providers will be taking on a greater portion of risk. In reward, these providers have an opportunity to receive a significantly higher net reimbursement. This transition is making for some interesting bedfellows as payers and providers join together to create new care delivery models such as Accountable Care Organizations (ACOs) and Patient Centered Medical Homes (PCMHs). These new models will be increasingly dependent on a robust HIT infrastructure to effectively measure quality, risk and performance, something that simply cannot be done effectively with the antiquated systems that are in place today in many healthcare organizations (HCOs).

Could Artificial Intelligence Destroy Radiology by Litigation Claims?

Dec 3, 2017• 2

By HUGH HARVEY, MD

We’ve all heard the big philosophical arguments and debate between rockstar entrepreneurs and genius academics – but have we stopped to think exactly how the AI revolution will play out on our own turf?

At RSNA this year I posed the same question to everyone I spoke to: What if radiology AI gets into the wrong hands? Judging by the way the crowds voted with their feet by packing out every lecture on AI, radiologists would certainly seem to be very aware of the looming seismic shift in the profession – but I wanted to know if anyone was considering the potential side effects, the unintended consequences of unleashing such a disruptive technology into the clinical realm?

While I’m very excited about the prospect and potential of algorithmic augmentation in radiological practice, I’m also a little nervous about more malevolent parties using it for predatory financial gains.