AI has been slaying it in almost every sector. Healthcare is benefitting a lot from voice based LLMs and ML. But this doesn’t mean we can trust them blindly.
Google DeepMind created an AI program named AlphaMissense, which predicts the harm a missense mutation can do, when a single DNA letter is altered. The tool, which leverages data from 71 million single-letter mutations affecting human proteins, uses machine learning to “understand” the language of proteins, helping it score the risk level of genetic changes.
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What AI is doing in synthetic biology is nothing short of revolutionary. Using AI, scientists are now programming cells to create new unseen proteins like coding software. We can expect groundbreaking changes in not only medicine, but also in sectors like agriculture, energy, and climate.
Also, recently, researchers from Edith Cowan University developed software that quickly scans bone density scans to detect abdominal aortic calcification (AAC), which is a predictor of cardiovascular events and other health risks. The software processed images with 80% accuracy and could revolutionize early disease detection during routine clinical practice.
In August, international researchers trained a ML model to identify autism spectrum disorder with 95% accuracy. While Stanford Medicine developed an algorithm that reviews images to determine a brain tumour’s aggressiveness, its genetic makeup, and effectiveness of surgery. “It’s sort of a decision support system for the physicians,” one researcher says.
Also, Scientists at the Osaka Metropolitan University developed an AI model that accurately identifies cardiac functions and valvular heart diseases using chest radiographs. The research could supplement traditional echocardiography, improve diagnostic efficiency, and be especially useful in settings lacking specialized technicians.
Startups in HealthTech are also upping their game with AI. London-based Ultromics trained its AI to detect a heart condition that human eyes can often not detect. In July, physician-entrepreneurs at Israel’s Sheba Medical Center started training AI to diagnose cardiac disease on a simple tablet, where the doctors don’t have to be heart experts. With a handheld scanner and tablet, non-cardiologists get a full diagnostic on 8 key heart readings. With its training data, the AI platform already has more experience than any living cardiologist, the physicians say.
In September, Xume, an Indian AI-powered grocery scoring and recommendation platform, tied up with, Microbiome.in (Microbiome Research Pvt Ltd), a research platform in the field of gut microbiome and, TruDiagno, a diagnostics startup. With a shared commitment to preventive healthcare, the trio seeks to empower individuals with individualised in-depth diagnostics and convert that information into actionable real-time intelligence.
This can help individuals to make informed choices based on the state of one’s gut microbiome and key diagnostic markers. Microbiome.in is the only private lab with an in-house Illumina and Nanopore (portable) Sequencer enabling unparalleled research on the role of gut microbiome, while TruDiagno adds advanced molecular diagnostic capabilities to the mix.
Imagine the power of understanding our microbiome and diagnostic markers to drive actionable intelligence; where the answer is not giving up our favourite foods but simply making better choices based on what our gut and body are telling us
Akshaye Jalan, Founder & CEO, Xume
“We’re all unique, so how can a generic solution mired in restriction be the answer to good health? Imagine the power of understanding our microbiome and diagnostic markers to drive actionable intelligence; where the answer is not giving up our favourite foods but simply making better choices based on what our gut and body are telling us. This is the future of health and wellness and what our partnership with Microbiome.in and TruDiagno endeavours to do.” said Akshaye Jalan, Founder & CEO, Xume.
In September, Oracle introduced voice-activated AI to hospitals, which will help doctors and clinicians to automate medical note-taking, order medications and view lab reviews while also more easily reviewing a patient’s medical record.
This is not about going from 10 clicks to seven clicks or six clicks to five clicks. This is about completely eliminating clicks, where we can and where it makes sense. That is not a tomorrow or that’s years away. That is a tomorrow that’s here
Mike Sicilia, executive vice president, industries at Oracle
“We’ve completely rethought how long it takes somebody to get their job done using the system. I think that we are on the verge of completely eliminating ‘pajama time’ as a result. This is not about going from 10 clicks to seven clicks or six clicks to five clicks. This is about completely eliminating clicks, where we can and where it makes sense. That is not a tomorrow or that’s years away. That is a tomorrow that’s here,” Mike Sicilia, executive vice president, industries at Oracle told the audience at the Oracle Health Conference.
But does this mean AI is your next doctor instead of a human?
All the above instances are brilliant examples of AI helping humankind become better at healthcare, but they’re also being done under supervision of experts, who are human.
Read more: Leveraging Machine Learning in healthcare chatbots for diagnostics support
The general online population has been turning to Dr. Google even before the Red Hot Chilli Peppers wrote Californication. But there’s a new doctor in town, Dr. ChatGPT. According to NPR, “the most recent version of ChatGPT made zero “grossly inaccurate” statements when presented with a standard set of eye complaints.”
However, questions still remain about how to fit in LLMs into healthcare with similar safeguards that are applied when introducing new drugs or medical devices.
