.svg)
Zoom has been raising user eyebrows lately—and not just during those "you're on mute" meeting moments. There's chatter about how their AI is eavesdropping on our meetings. While we’re all for pushing boundaries, sometimes a touch of digital etiquette goes a long way. And with the rise of so many new generative AI tools, data safety is certainly becoming an increasingly hot topic.
Speaking of AI's insatiable curiosity, OpenAI's latest web crawler is about to turbocharge AI models—basically giving ‘GPTBot’ the keys to the internet. But OpenAI isn’t the only company riding the rollercoaster, Disney's taking a strategic bet and assembling an AI task force to develop in-house (yes, the Mickey Mouse ClubHouse) AI applications, ensuring their next tech adventures are more 'Magic Kingdom' and less 'Tower of Terror’.
And while theme parks might be the stuff of childhood dreams, we're daydreaming about a future where AI and healthcare go hand in hand—luckily Duke University and Microsoft are making moves. Their 5-year partnership aims to harness AI's potential, turning those dreams into diagnostics and data-driven decisions. Fun fact: the healthcare industry has been the AI deal-making champion since 2015. Who knew?
GEN AI
Top 3 Use Cases for Generative AI in Healthcare
A couple of weeks ago, in an A.Team webinar titled "Demystifying AI in Healthcare," a panel of experts parsed generative AI's medical prospects, discussing the new technology's role in everything from personalized medicine to drug discovery to the tedium of medical red tape, distilling the imminent use cases from the moonshots.
The three panelists emphasized one central tension: Generative AI can improve doctors' quality of life, the drugs they prescribe, and the care they provide patients—but only if industry leaders and regulators find ways to navigate the thorny legal and compliance challenges.
"How are we going to protect patient data? That's the million-dollar question," said Ed Kopetsky, former CIO of Stanford Children’s Health.
The stakes are enormous. Here are the most feasible—and most urgent—near-term targets for those implementing AI in health systems:
Personalizing primary care
Our genes, our personal and familial histories, even the way our bodies break down drugs—these all differ from person to person. Yet with few exceptions, doctors rarely provide such personalized care. It simply isn't feasible: The research is time-consuming, and the relevant data is scattered across many years of medical records.
Up to 80% of patient data is unstructured, Kopetsky estimated, and often gets lost or overlooked. Even experts get neglected, he said: Kopetsky's father died of kidney disease at age 42. "I've been treated for 14 years, and none of that has been factored into my treatment," he said.
Large language models can rapidly digest and interpret such unstructured information, helping overloaded doctors provide personalized medicine to patients even if their face-to-face time averages just eight minutes.
"We have a huge store of data that can be used way more optimally—almost magically—in 30 seconds," said Kopetsky. "Today's noise is tomorrow's critical information."
Reducing administrative burden
Clinicians are often swamped with administrative duties that eat into their valuable time with patients. AI is already being developed to ease this burden. Amazon's HealthScribe and the partnership between Epic Systems and Microsoft's Nuance Communication lead the way with so-called Ambient Documentation, which listens to doctors' interactions with patients, makes notes, and even suggests diagnoses. AI allows doctors to refocus on patient care by taking over these routine tasks.
Goal number one, according to Ohad Zadok, co-founder and CTO of Alike.Health, is helping practitioners "spend less time in front of a computer and more time in front of patients."
Streamlining drug discovery
"Better prediction and prevention of diseases" was what the webinar's audience overwhelmingly found the most exciting potential of AI—with over 50% giving that answer in a mid-discussion survey question that asked, "What aspect of your healthcare experience do you think could be most improved with AI?
Drug discovery holds the most exciting potential, agreed the panelists. Just as large language models could help doctors sift through unstructured personal data on behalf of their patients, AI tools can also analyze vast and complex data sets connected to pharmaceutical trials, identifying potential drug targets and predicting their interactions with possible medications in new ways. This analysis could lead to the rediscovery of many such "difficult, orphan, and rare drugs and therapeutics," noted Mida Pezeshkian—and at rapid speed.
"You can achieve things 5 to 10 times faster than traditional methods,” Zadok said.
"A lot of data scientists will need to look for a job," said Zadok. "AI cannot replace doctors, though, at least for now," he added with a chuckle.
EVENTS
Send Us to SXSW!
Wondering what's happening in the tech world post 'Great Betrayal'?
We're diving deep, but we need your help to bring the conversation front and center at SXSW!
Our panel "Life After Big Tech: Where Are Laid Off Workers Now?" dives into the rise of freelance work, the changing tech landscape, and how companies can navigate these uncertain times. We’ll be discussing:
- The evolving dynamics of talent and compensation in the tech world.
- Why top tech talents are leaning towards freelance.
- How this shift is reshaping company strategies.
Vote now to help bring our panel to SXSW!
MISSION MUST-READS
- 3 Healthtech VCs on Managing Burn and Raising in a Downturn
- Why Enterprise Healthtech Pilots Fail—And How to Fix It
PARTING MEME
.jpeg)
.jpg)
.jpg)
