How to write a headline involving AI.

When you have your AI model done, validated and published, it’s time to communicate it to the world.
 
And the important thing to realize is that you can go from less sensationalist to more sensationalist as you see fit. 
 
 
Level 1: scientific purist.
 
The biomarker NG17 may have implications for the development of hypophosphatemia.
 
Only later in the body of the text will you mention that Random Forest (a form of machine learning) was used for its development.
 
Pros: disease experts will respect you.
Cons: you reach 0.001% of the audience.
 
 
Level 2: you still retain dignity, but you are already starting to have fun.
 
Researchers develop a predictive model for the development of hypophosphatemia.
 
Again, it is in the body of the message when you mention that machine learning has been used. Moreover, you still stress that it is researchers, not machines, who do things.
 
Pros: no one spits in your face at the congress.
 
Cons: you are still only reaching people with an interest in this pathology.
 
 
Level 3: it’s all about impact, not accuracy.
 
A machine learning model is able to predict the development of hypophosphatemia.
 
Bye bye humans. Here we have already crossed the abyss, by putting the machine learning concept in the headline.
 
Pros: journalistic arrival level is high and there will be many likes on Linkedin.
Cons: your fellow residents hate you .
 
 
Level 4: what the hell, we are here to play.
 
An Artificial Intelligence predicts who will develop metabolic diseases.
 
There is no shame. AI is presented as an individual and autonomous entity that can destroy humanity at will. Moreover, you generalize, as if it can maneuver in any disease. 
 
Pros: you might get it published in general media.
Cons: you can never set foot in a hospital or apply for a serious grant again in your life.

Look,making an AI algorithm has its own set-up. 

 
Then you have to publish it, communicate it, use it with the agency or administration you are interested in… and even implement it in clinical practice.
 
 

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