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  • Updated: March 25, 2023

Bionic Health: Role Of AI, GPT-4, ML In Preventive Care

Bionic Health: Role Of AI, GPT-4, ML In Preventive Care

Image credit: Bionic Health

At a time like this when talks about artificial intelligence (AI), OpenAI ChatGPT-4 (GPT-4), and machine learning (ML) seem to be occupying centre stage everywhere, there's a need to stress that in the field of medicine, AI is not a novel tool.

Yes, AI has been used for years in the field of healthcare and it has continued to grow tremendously each year with its ability to advance medicine and research. 

Indeed, when it comes to leveraging a patient’s genetic history, location, environmental factors, lifestyle, and habits to determine a plan of action for treatment, precision medicine holds sway.

For this, for example, AI has been successfully exploited to classify problems using different algorithms to solve precision medicine problems such as accurate disease diagnosis, detection and prediction, and treatment optimization.

Moreover, precision medicine is not completely possible without the addition of machine learning algorithms to assist in the process.

In this case, ML, which is an application of AI to learn and upgrade from experiences without an explicit need for programming, specializes in the development of application-specific computer programs which can retrieve patients' data as a use case to learn and train itself.

The most commonly used ML algorithms in medicine include SVM, deep learning, logistic regression, DA, decision tree, random forest, linear regression, etc.

Putting all of this together with GPT-4 based on recent trends, patients can engage incredibly well with an AI-enabled health sector to figure out their health cases and take first-degree first-aid measures. 

Based on the above preview, it's now clear why a startup, Bionic Health, is taking a giant leap to exploit these dynamic technologies in the health sector.

Bionic Health's Leverage

Put in a matter-of-fact way, the worlds of technology and medicine are making big bets on AI playing a central role in the delivery of healthcare in the future.

Recently, a startup out of Durham, North Carolina, called Bionic Health — built by two early movers in the commercializing of AI — is throwing its hat into that ring to build out its approach.

The startup has raised $3 million in seed funding to create what it describes as an “AI health clinic”: people can get bloodwork and other diagnostics carried out and monitored, and then an AI — built on OpenAI’s GPT-4 and other large language and machine learning models — provides personalized insights based on the data points coming out of these assessments. 

The initial aim is to build out preventative health services rather than primary care for people who, for example, are experiencing chronic pain or a virus.

Longer term, co-founder and CEO, Robbie Allen, believes Bionic Health has the potential to extend into all aspects of doctor-patient care.

“There are just so many areas that can be improved,” he said, highlighting the shortage of both general practitioners and specialists across both developed and developing world communities.

“We are losing primary care, and doctors, every day. It’s unacceptable that you can’t get appointments that easily.

"We may need to automate more of that out of necessity.” Using AI to take on the work of specialists, meanwhile, could also evolve over time, synthesizing more data from across specializations to deliver more accurate insights.

“The first line of speciality care could be tech-driven,” he added.

Bionic Health’s first clinic is also, effectively, its first lab: as the startup trains its AI and figures out where best it can be put to work, it will have actual, human doctors involved working alongside that AI and providing feedback to better shape it.

AI-Assisted Care technology is designed to assist clinicians with clinical evaluation tasks.

Allen said. “We believe it can significantly improve the efficiency and accuracy of the diagnosis and treatment process.”

IDEA Fund Partners, Studio VC, Alumni Ventures, Tweener Fund, AI Operator’s Fund, and Operator.VC all participated in this round.

Allen said that originally the aim was to raise $2 million but interest in the startup was high.

That is not just because “generative AI” is all the rage right now (although that will definitely be figured out here); Allen and Pelo have a prescient and proven track record when it comes to building lasting AI startups.

Allen’s previous company, Automated Insights, built one of the first generative AI services back in 2007, creating prose out of data and other prompts.

Years before CNET found itself embroiled in an AI-writing controversy, the Associated Press invested in and used Automated Insights to write hundreds of articles.

The startup is now owned by Vista Equity and works across a big range of enterprise use cases.

Pelo, meanwhile, founded a company called iScribes, which described itself as an “ambient documentation” company aimed at healthcare.

It was eventually acquired by Nuance, which itself was acquired by Microsoft, where Pelo worked as chief clinical product officer just until this month, leaping to found Bionic Health with Allen (who had been on iScribes’ board: Durham AI tech guys stick together, I suppose).

The GPT-based health documenting service announced just yesterday by Microsoft was based on technology Pelo developed at iScribes and oversaw at Nuance and then Microsoft.

There are a lot of areas where AI might potentially play a role in the world of healthcare: robotics, administrative tools, drug discovery, pathology, and clinical interactions are all areas that have seen activity in recent years.

However, not everyone thinks that clinical roles are the most ideal of these — not now and possibly not ever.

Alexandre Lebrun, the co-founder of another AI healthcare startup called Nabla — coincidentally Lebrun also sold a previous AI startup to Nuance years ago — believes that there is just too high a risk with AI being wrong, and that’s too serious to consider in healthcare scenarios.

Nabla earlier this month released Copilot, which focused just on providing administrative assistance, not clinical advice, to clinicians and patients.

Allen believes that development will be much more of a continuum and that the evolution will be pushed not just by market and social forces — healthcare being “broken” while ever more people are demanding ever more services — but also by AI technology that has been rapidly evolving.

Allen said he and Pelo first started thinking about what has become Bionic Health with theoretical ideas about “automated doctor-patient” interactions but things changed with early looks at what GPT-4 could do (recall Pelo was at Microsoft, which backs GPT creator OpenAI, until just this month).

“As GPT-4 started to become available, it really changed the dynamic,” Allen said, with “a speed, and a much higher percentage [of accuracy] than even a few months ago.”

Providing personal health data using a model like GPT-4, combined with a model for specific guidance and treatments, is already very high even without improvement, he added.

“And when GPT-5 comes out it could be another significant step forward. I think Nabla might be underestimating the technology.”

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