Artificial intelligence in diagnostics is making strides. Not only making diagnostics cheaper but also faster and more accurate. And it allows many medical facilities access to quality diagnostics that they might not have otherwise. But what if everyone could access AI diagnostics? What if we had AI diagnostics on our phones?
Traditional Diagnostics Are Unrealistic
According to some studies, inaccurate or delayed diagnoses cause 10% of deaths. However, autopsy studies put the number closer to 20%. Regardless, millions of people die from easily treatable conditions because they don’t have access to reliable diagnostics.
For example, a child might have pneumonia. But without reliable diagnostics, a nurse or doctor might diagnose it as a cold. Or someone with TB goes undiagnosed and untreated while infecting those around them. Without treatment, these conditions cause needless suffering and death.
Medical diagnostics rely on signs and symptoms along with tests to identify diseases. Even with years of training, diagnostics is often grueling and time-consuming. And the demand for experts far outweighs the supply.
Additionally, access to diagnostics is complicated. Many medical facilities lack resources. Laboratory machines cost a lot of money, and facilities need infrastructure and educated operators. Therefore it’s unrealistic to bring to remote rural areas.
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AI Diagnostics On Our Phones Could Reshape Healthcare
Everyone has a smartphone. If we have AI diagnostics on our smartphones, we can eliminate millions of unnecessary deaths.
We have the technology. Recent AI advances make it possible for Machine Learning algorithms to diagnose diseases. Algorithms use real examples and learn to see patterns as a doctor would. They also improve their learning over time in an autonomous fashion.
Machine Learning depends on thousands of concrete examples. And the problem is, we don’t have enough, yet. However, by gathering high-quality samples, AI can improve to the point where everyone can access diagnostics on their phones.
Machine Learning is especially helpful where diagnostic data is digital, for example, CT scans, electrocardiograms, and cardiac MRI images.
Furthermore, AI can classify skin lesions from photos or find indicators of diabetic retinopathy in eye images.
Since there are lots of high-quality digital data for these cases, algorithms are fast becoming as good at diagnostics as clinicians. But, the algorithms can make a diagnosis in a fraction of the time. What’s more, it’s inexpensive to reproduce.
Hyfe is building classification algorithms that will solve the problem of slow, inaccurate, difficult-to-reach diagnostics. Accurate cough classification algorithms will be revolutionary. It aims to improve diagnostics reliably and affordably for anyone with access to a smartphone. At the same time, it will address inequities in access to care.
By running Hyfe, any smartphone can become a valuable diagnostic device, particularly in settings with poor primary health care infrastructure and limited access to quality diagnostics.
So, what if we had AI diagnostics on our phones? We’ll have affordable, reliable diagnostics globally. And eliminate millions of deaths due to misdiagnosis or lack of any diagnosis. We already have the technology, and we’re working on the samples. It’s just a matter of time until everyone can access accurate diagnostics from anywhere in the world.