Venture Cash Is Pouring Into AI that Can Diagnose Diseases. Doctors Aren’t Sure They Can Trust It.

Keerthi Vedantam

Keerthi Vedantam is a bioscience reporter at dot.LA. She cut her teeth covering everything from cloud computing to 5G in San Francisco and Seattle. Before she covered tech, Keerthi reported on tribal lands and congressional policy in Washington, D.C. Connect with her on Twitter, Clubhouse (@keerthivedantam) or Signal at 408-470-0776.

Venture Cash Is Pouring Into AI that Can Diagnose Diseases. Doctors Aren’t Sure They Can Trust It.
Ian Hurley

Medical imaging AI, which can help diagnose health problems doctors don't always see, is only getting more sophisticated—and more lucrative. Just last month, Tel Aviv-based Aidoc raised $65 million for its AI-powered medical imaging platform and other local companies are attracting investors at a rapid clip.


The software can find, and in some cases, diagnose polyps, tumors or anomalies that may otherwise go undetected by the human eye – a feat that has the potential to save lives. Beyond its most promising attributes, AI-driven technology could also dramatically decrease wait times at hospitals and doctors' offices by automating some of the most tedious work, allowing doctors to see and treat more patients. But critics of the unregulated technology say results can be inconsistent.

Brendan Burke, an emerging tech analyst at Pitchbook, estimates investment in the space has skyrocketed, from $1.6 billion in 2019 to $2.6 billion in 2020.

"[Venture capitalists] have certainly seen enough adoption to justify substantial investments," Burke said. "But there's still uneven adoption overall and a degree of skepticism from health care providers. "

The money is pouring in because most illnesses are diagnosed with a terrifying cocktail of subjectivity and luck, and a hard-to-find tumor could rear its ugly head when it's too late, forcing clinicians to scramble to use invasive (sometimes dangerous) procedures to course correct.

Paul Grand, founder and CEO of MedTech Innovator, a medical technology startup accelerator said interest is gaining traction because investors see the potential for a breakthrough technology — even if it isn't fully proven yet.

"They're not looking for little incremental improvements when they make investments as VCs, they're looking for game-changing, industry needle-moving investments," he said.

Irvine-based Docbot, a gastrointestinal AI startup that has raised $6.5 million according to Pitchbook, developed Ultivision AI to find polyps that could turn cancerous. Most diagnoses come from a doctor's ability to find them through a camera inserted into the GI tract. Created by gastroenterologist William Kames, Docbot uses AI to point out faded or small polyps through the camera lens.

"By doing this, you'll catch more polyps, and thus the colonoscopy will have a higher performance rate in hopefully catching more polyps, so a patient would have less risk of getting colon cancer afterwards." said Docbot CEO Andrew Ritter.

After feeding 50,000 colonoscopy videos through a machine learning algorithm, Docbot put Ultivision AI up next to a panel of physicians to detect polyps in a slew of videos. The AI found 61% more polyps than the panel.

Now, the AI has been trained on more than 10 million images.

Another AI-based tool, Woodland Hills-based Eyenuk, received FDA approval as a medical imaging AI device that can diagnose diabetic retinopathy 10 months ago. The device has been trained on more than two million images and is scattered across 15 different institutions in the US.

Eyenuk's device became useful during the coronavirus pandemic. Nose-to-nose contact is often unavoidable for opthamologists who need to conduct eye exams, but the device could operate autonomously, taking photos of a patient's eyes and diagnosing the problem in a span of minutes.

"[Doctors] want AI to prescreen people's eyes in the community," Frank Cheng, president of Eyenuk, said. "...if there is a need for evaluation and treatment, they then jump in to more efficiently treat the patient."

Eyenuk Inc.'s AI-based diabetic retinopathy screening software was tested in a study on cost-effective mass retinal screening.

Doctors Remain Skeptical

Despite the sweeping promises of medical imaging AI, doctors remain largely distrustful of the tech. A survey from the American College of Radiology found that only 30% of doctors use medical imaging AI, and a study presented to the FDA found that 95% of clinicians largely think AI is inconsistent or doesn't work at all.

"Sometimes these machine learning models are so sophisticated, it's really hard to tell how a program actually came to its decision," said Ritika Chaturvedi, a precision medicine expert at the USC Schaeffer Center. "How is that physician to know whether to evaluate their own judgment or use the AI's recommendation?"

With most medical imaging AI, a doctor or a startup will collect a set of reference images or videos of whatever it is they want to target—rashes on the skin, tumors in the body, or x-rays of bone fractures—which they then feed through a machine learning algorithm that uses those images to learn what to look for. The algorithm marks different patterns it finds in the images, such as shape or color, to build a framework for what it should look for. When the algorithm is calibrated to detect images at the level of accuracy the team desires—sometimes 80% accuracy, sometimes 60%—the team applies the machine learning algorithm to an unknown image to see if it can catch it.

But the lack of standardization in medical imaging AI makes it difficult for clinicians to know if they can trust the technology. There are no standards on how many reference images need to be used to train the AI (though the more, the better). There is also no rule that dictates a machine learning algorithm is satisfactory at 80% accuracy, or 60% accuracy. Nor are protocols in place for when a doctor disagrees with an AI's assessment.

"Because this field is so new, people are just now starting to grapple with the ethics," Chaturvedi said.

When a specific AI software is approved by the Food and Drug Administration, it doesn't undergo re-approval when it adds images or videos to its machine-learning model, which can change how the AI performs. Datasets are often not available to the public to review if the data is representative of the population.

"The adage is in computer science, garbage in, garbage out," Chaturvedi said. "So if your training data set is highly biased, then your outputs are going to be highly biased."

Grand says there's an adoption phase with every new technology, and medical imaging AI will one day reach a point where it could be considered negligent for doctors not to use it.

"It could be five years, 10 years, but that's the phase we're going to be in where doctors go, 'Okay, AI is a new tool for me to be a better doctor, '" Grand said.

Indeed, there may soon come a time when doctors embrace medical imaging AI, when residents are trained to use the technology in hospitals and clinics and when medical organizations will consider AI to be as much of a staple as a stethoscope or an MRI to diagnose. But in order for that to happen, experts say, the data needs to be unequivocally clear that AI is beneficial, and regulations need to be put in place to encourage board adoption.

"You've diagnosed the cancer," Chaturvedi said. "But if you can't treat it, then what's the point?"

Lead art by Ian Hurley.

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How the 'Thrift Haul' Boosted Secondhand Ecommerce Platforms

Lon Harris
Lon Harris is a contributor to dot.LA. His work has also appeared on ScreenJunkies, RottenTomatoes and Inside Streaming.
How the 'Thrift Haul' Boosted Secondhand Ecommerce Platforms
Evan Xie

If you can believe it, it’s been more than a decade since rapper Macklemore extolled the virtues of thrift shopping in a viral music video. But while scouring the ranks of vintage clothing stores looking for the ultimate come-up may have waned in popularity since 2012, the online version of this activity is apparently thriving.

According to a new trend story from CNBC, interest in “reselling” platforms like Etsy-owned Depop and Poshmark has exploded in the years since the start of the COVID-19 pandemic and lockdown. In an article that spends a frankly surprising amount of time focused on sellers receiving death threats before concluding that they’re “not the norm,” the network cites the usual belt-tightening ecommerce suspects – housebound individuals doing more of their shopping online coupled with inflation woes and recession fears – as the causes behind the uptick.

As for data, there’s a survey from Depop themselves, finding that 53% of respondents in the UK are more inclined to shop secondhand as living costs continue to rise. Additional research from Advance Market Analytics confirms the trend, citing not just increased demand for cheap clothes but the pressing need for a sustainable alternative to recycling clothing materials at its core.

The major popularity of “thrift haul” videos across social media platforms like YouTube and TikTok has also boosted the visibility of vintage clothes shopping and hunting for buried treasures. Teenage TikToker Jacklyn Wells scores millions of views on her thrift haul videos, only to get routinely mass-accused of greed for ratching up the Depop resell prices for her coolest finds and discoveries. Nonetheless, viral clips like Wells’ have helped to embed secondhand shopping apps more generally within online fashion culture. Fashion and beauty magazine Hunger now features a regular list of the hottest items on the re-sale market, with a focus on how to use them to recreate hot runway looks.

As with a lot of consumer and technology trends, the sudden surge of interest in second-hand clothing retailers was only partly organic. According to The Drum, ecommerce apps Vinted, eBay, and Depop have collectively spent around $120 million on advertising throughout the last few years, promoting the recent vintage shopping boom and helping to normalize second-hand shopping. This includes conventional advertising, of course, but also deals with online influencers to post content like “thrift haul” videos, along with shoutouts for where to track down the best finds.

Reselling platforms have naturally responded to the increase in visibility with new features (as well as a predictable hike in transaction fees). Poshmark recently introduced livestreamed “Posh Shows” during which sellers can host auctions or provide deeper insight into their inventory. Depop, meanwhile, has introduced a “Make Offer” option to fully integrate the bartering and negotiation process into the app, rather than forcing buyers and sellers to text or Direct Message one another elsewhere. (The platform formerly had a comments section on product pages, but shut this option down after finding that it led to arguments, and wasn’t particularly helpful in making purchase decisions.)

Now that it’s clear there’s money to be made in online thrift stores, larger and more established brands and retailers are also pushing their way into the space. H&M and Target have both partnered with online thrift store ThredUp on featured collections of previously-worn clothing. A new “curated” resale collection from Tommy Hilfiger – featuring minorly damaged items that were returned to its retail stores – was developed and promoted through a partnership with Depop, which has also teamed with Kellogg’s on a line of Pop-Tarts-inspired wear. J.Crew is even bringing back its classic ‘80s Rollneck Sweater in a nod to the renewed interest in all things vintage.

Still, with any surge of popularity and visibility, there must also come an accompanying backlash. In a sharp editorial this week for Arizona University’s Daily Wildcat, thrift shopping enthusiast Luke Lawson makes the case that sites like Depop are “gentrifying fashion,” stripping communities of local thrift stores that provide a valuable public service, particularly for members of low-income communities. As well, UK tabloids are routinely filled with secondhand shopping horror stories these days, another evidence point as to their increased visibility among British consumers specifically, not to mention the general dangers of buying personal items from strangers you met over the internet.

How to Startup: Mission Acquisition

Spencer Rascoff

Spencer Rascoff serves as executive chairman of dot.LA. He is an entrepreneur and company leader who co-founded Zillow, Hotwire, dot.LA, Pacaso and Supernova, and who served as Zillow's CEO for a decade. During Spencer's time as CEO, Zillow won dozens of "best places to work" awards as it grew to over 4,500 employees, $3 billion in revenue, and $10 billion in market capitalization. Prior to Zillow, Spencer co-founded and was VP Corporate Development of Hotwire, which was sold to Expedia for $685 million in 2003. Through his startup studio and venture capital firm, 75 & Sunny, Spencer is an active angel investor in over 100 companies and is incubating several more.

How to Startup: Mission Acquisition

Numbers don’t lie, but often they don’t tell the whole story. If you look at the facts and figures alone, launching a startup seems like a daunting enterprise. It seems like a miracle anyone makes it out the other side.

  • 90% of startups around the world fail.
  • On average, it takes startups 2-3 years to turn a profit. (Venture funded startups take far longer.)
  • Post-seed round, fewer than 10% of startups go on to successfully raise a Series A investment.
  • Less than 1% of startups go public.
  • A startup only has a .00006% chance of becoming a unicorn.

Ouch.

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From The Vault: VC Legend Bill Gurley On Startups, Venture Capital and Scaling

Spencer Rascoff

Spencer Rascoff serves as executive chairman of dot.LA. He is an entrepreneur and company leader who co-founded Zillow, Hotwire, dot.LA, Pacaso and Supernova, and who served as Zillow's CEO for a decade. During Spencer's time as CEO, Zillow won dozens of "best places to work" awards as it grew to over 4,500 employees, $3 billion in revenue, and $10 billion in market capitalization. Prior to Zillow, Spencer co-founded and was VP Corporate Development of Hotwire, which was sold to Expedia for $685 million in 2003. Through his startup studio and venture capital firm, 75 & Sunny, Spencer is an active angel investor in over 100 companies and is incubating several more.

Bill Gurley in a blue suit
Bill Gurley

This interview was originally published on December of 2020, and was recorded at the inaugural dot.LA Summit held October 27th & 28th.

One of my longtime favorite episodes of Office Hours was a few years ago when famed venture capitalist Bill Gurley and I talked about marketplace-based companies, how work-from-home will continue to accelerate business opportunities and his thoughts on big tech and antitrust.

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