The untold truth of women’s health and why AI is the only solution.
I still remember the day I sat with 5 of my classmates and started talking about Artificial Intelligence.
As you can already guess, they had no idea what it was. But, what I found worse than that, is that when I started talking about the implications of AI, they were only interested when I was talking about self-driving cars and video games.
Self-driving cars are cool. But, the problem is we are disregarding more important problems.
AI is a revolutionary technology that is an extension of the human mind and has the potential of solving some of the world’s largest problems.
This article is broken down into 4 main sections:
- Why we should care about Women Health
- Importance of Diagnosis
- How AI can help?
- So what does this mean?
Why should we care about women’s health?
For the longest time now we thought women were the same as men.
From a medical perspective, not social.
There were just two main differences, the fact that women had a vagina and breasts.
- women are 4 times more likely to be diagnosed with Multiple Scleroses
- 70% of women are more likely to develop lung cancer
- 50% of women don’t get the correct heart failure treatment
- women are represented in less than 20% of clinical trials of treatment
Well, as you can tell. Women are a lot more different than men.
We also know that women run the world.
“Who run the world? GIRLS! Who runs this motha? GIRLS”
But no literally, they do run the world. Women make household and hospital decisions.
- 83% of women have major buying power in their households
- 90% of women are primary healthcare decision-makers
Women are taking medication dedicated to men.
Imagine having been told by your parents (people you trust so much) to take a cigarette a day because it will “help” with your mental health.
You would most likely believe them and take it. I would, I mean they’re your parents. However, little did you know it was the worst thing you could be doing to yourself and would make your mental health 10x worse.
This is what is happening to women across the globe every single day. They trust that doctors will supply what is best for them.
When in reality, we are taking medication suited towards men. Women are represented in less than 20% of clinical trials that means medications that we are taking has a 20% likelihood of working, the rest is just luck.
What I find ridiculous is that we are living in a society that prides itself on all the equal rights we as women have, however, what we fail to see is that our healthcare was never taken to account and our system has failed to provide women with basic health care treatments.
The Importance of Diagnosis
Diagnosing conditions and diseases can lead to more accurate solutions, but don’t we already have “ok” diagnostic methods?
Nope!
Women don’t get accurate medication because the process to understand and diagnose diseases like depression, and MS is much more complicated and not efficient, therefore professionals prefer to use old data.
The sample people they have from 100 years ago are the same way they are classifying today.
100 years ago a group of people were doing clinical trials, only 12% of them were girls. The data that was collected 100’s of years ago, is how we are developing solutions today.
I know it’s ridiculous!
This is why if we can detect what conditions and diseases people are likely to have in the future. We can prevent them from happening, either with medication or homeopathy.
Why go through the struggle of taking medications and going to check-ups to try to let go of your condition when you can prevent it from happening in the first place?
How do we do this?
Right now, if someone has symptom’s or gets an x-ray, that would be the only way to tell if someone has a disease.
But, believe it or not! Mental health disorders have it much worse.
Currently diseases such as depression are diagnosed through “talking” to a professional.
What they don’t seem to understand is that most often patients are biased when they are talking. The accuracy of diagnosing depression based off of a “talk” is less than 18%.
What’s even more ridiculous is that About twice as many women as men experience depression.
Imagine going to the store and buying a brownie mix. The box says there are many chocolate chips in the mix.
So later that evening, you unpack the box and you only find 5 chocolate chips. That’s disappointing because there is nothing you can do about it.
But, what if there was a way that could tell you the precise amount of chocolate chips there were there before you bought the box?
This is where AI comes in, and how we can diagnose diseases before there are any symptoms of it to hopefully prevent them from happening.
You have probably heard “what if we can detect cancer 10 years before, you actually have cancer?” If you could tell the likelihood on someone developing cancer, then there is a 95% chance that you can prevent it from happening.
As well, this can also lead to better and more personalized medication! Therefore we can tackle the inequities in our healthcare system by giving women accurate diagnostics and medications.
To start, let’s breakdown the basics of AI!
There are two different types of AI, Weak AI which allows computers to outperform humans in some very specific tasks and Artificial General Intelligence, the ability of a machine to perform the same intellectual tasks as a human being (we are far from reaching it).
Artificial Intelligence is mainly based on two pillars: Symbolic Learning and Machine Learning.
Machine Learning
Machine Learning, is a system capable of taking large amounts of data, developing models that can successfully classify them and then make predictions with new data.
ML has many different sub-categories, such as deep learning, supervised learning, and unsupervised learning.
If you were to predict the likelihood of an outcome from a certain piece of data, Machine Learning would be used, as ML is classified as a way to train a neural network using algorithms to do a specific task without additional human interaction.
Dependant on the type of data. We can build a machine learning model that would classify the data to diagnose diseases and conditions.
For example, if we were looking into early diagnosis of autism we would find data from your gut microbiomes, you could take that data and cluster together with the guts with ASD and not with ASD. Therefore, the next time you would input someone’s data, we could diagnose if they have autism through a neural network or random forest classifier.
So what does this mean for women?
If we can predict the likelihood of someone developing a disease or condition we can prevent it from happening.
Women aren’t getting the right medication as often medications and treatment is suited towards men. This is why if earlier on the accuracy of someone developing a disease can be detected we can give more personalized treatment methods.
Let’s start unlocking AI’s potential, and start prioritizing women’s health.
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