The future of medical treatment lies where AutoML and life scientists meet

Alzheimer’s Disease (AD) is the fifth leading cause of death for those aged 65 plus. There is currently no definitive diagnosis short of autopsy, and scientists are racing the clock against the arrival of the oldest average population in history. With this push comes an abundance of study data, and there just aren’t enough data scientists to keep up with analyzing it all.  Enter automated machine learning (autoML), which solves this problem by automating the machine learning process end-to-end. 

What is AutoML? 

More than 70 years after the invention of the first computer, these are no longer just objects of wonder. And, they’ve become extremely intelligent. Machine learning is the study of computer algorithms that improve automatically through experience. Sounds pretty smart, right? These algorithms are patterns that can provide critical insight into diseases such as Alzheimer’s. However, in order to be useful, you need a large set of them doing many different sophisticated processes each, running thousands of combinations on your data, choosing the best feature sets to give prominence to, tweaking for best predictive performance…and all that has to be done by a scientist who understands what the outcome means. It’s sort of combining two different disciplines into one; biology and computer science into one. While such a discipline does exist, it’s your bioinformatician, the whole process of building machine learning models is no easy feat. It usually takes a lot of time, often months, and programming knowledge to choose the right algorithms, tweak for hyperparameters, and in the end, create a predictive model that gives you the best performing results for your problem. 

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