Gear Up Your AI: Fine-Tuning LLMs
April 29, 2016

How Visual Recognition Is Used to Augment Doctors and Diagnosis

Table of Contents:

i-Nside is a worldwide leader in endoscopic technology. With a small device you can attach to any smartphone, i-Nside can take professional-grade medical images of the human ear and use them to diagnose problems. With so many medical images on file, i-Nside wanted to build a diagnostic platform that would be able to assist doctors in identifying ear problems.

1. AVOID TECHNICAL DEBT: What’s the best way to build custom visual recognition into your product?
Getting started with visual recognition and machine learning can be both challenging and expensive. As a small team, i-Nside needed a cost-effective and easy way to build very advanced artificial intelligence technology into its product without incurring technical debt.

2. TRUSTWORTHY RESULTS: How do you ensure that your visual recognition results are accurate?
The stakes are pretty high when it comes to visual recognition and something as life-changing as a medical diagnosis. i-Nside needed a solution that would not only provide accurate results for a very esoteric data set (pictures of the insides of ears) but would also be able to improve with more training.
“Clarifai differentiates itself by providing tools and solutions that businesses and healthcare specialists can use right now, not in ten years. With Clarifai built into our product, we’re achieving 99% accuracy with our visual diagnostic tool!” – Dr. Laurent Schmoll, i-Nside CEO


i-Nside uses Clarifai’s visual recognition solution to build an accurate medical diagnosis platform that helps doctors all over the world provide the best medical care to their patients.
Diagnosing ear problems is a very specialized field of expertise within medicine. General practitioners usually refer people with ear problems to Ear, Nose, and Throat (ENT) specialists. i-Nside wanted to build a diagnostic tool that would assist general practitioners and nurses to identify and treat ear problems accurately, thereby making the best medical care accessible to anyone in the world.
With over 100,000 ear images collected from their widely distributed endoscopic tool, i-Nside asked Clarifai to build a custom visual recognition model especially for ear pictures and video. Now, Clarifai’s visual recognition technology powers the software layer in i-Nside’s line of endoscopic hardware, enabling the tool to not only take pictures of the ear but also to analyze the results – all in one small, affordable, mobile package that anyone can use!


Minimum costs, maximum results
i-Nside had to prove that an assisted diagnosis tool could work before they could get the funding and approvals to put it into production. However, like many startups, they faced a “chicken or egg” problem – they didn’t have the funding to build an expensive A.I. visual recognition product, but they wouldn’t receive more support unless they proved visual recognition worked.
i-Nside partnered with Clarifai to create a cost-effective custom visual recognition model that they built into a beta product to demonstrate the power and accuracy of visual recognition without breaking the bank.

A custom model for unique needs
While Clarifai’s core model can recognize over 11,000 general concepts, ear diseases unsurprisingly are not among those core tags. i-Nside needed a special custom model built for the sole purpose of analyzing ear patterns.
Clarifai’s team of data scientists used their expertise to train a custom model on i-Nside’s batch of ear images. It only took a couple of weeks for the custom model to be fully trained to recognize ear problems with near perfect accuracy. The i-Nside team was then able to access the custom model through Clarifai’s API with just a few lines of code.
“We looked into IBM Watson, but they were not a cost-effective option. Clarifai gave us stellar customer support and a simple, well-documented API that allowed us to plug-and-play without incurring financial or technical debt.”

Changing the world, one image at a time
Now that Clarifai’s custom model is powering their endoscopic diagnosis tool, i-Nside can deliver accurate diagnoses to doctors in every corner of the world. Traditionally underserved markets like some parts of Africa, Asia, and South America now have access to the best specialist knowledge in medical care. As i-Nside continues to collect more endoscopic imagery, Clarifai’s model gets smarter and delivers even more accurate results by learning from the feedback.
And endoscopic diagnoses are just the start. i-Nside is hoping to expand both their imaging hardware and their artificially intelligent diagnosis tool to other fields of medicine like oncology (cancer) and radiology (medical imaging like x-rays).
“Our diagnosis tool is meant to augment doctors, not replace them. We decided to work with Clarifai because our philosophies are very aligned – we believe that artificial intelligence can amplify human intelligence, but it’s not a substitute.”

DIY with Clarifai
Now that you’ve been inspired by i-Nside’s mission to change the world, it’s time to build your own app. Clarifai’s core model includes tags for over 11,000 concepts you can apply to your business. All it takes is three simple lines of code – sign up for a developer API account to get started for free!

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