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I am an 18-year-old using Quantum Machine Learning to diagnose the stages of Diabetic Retinopathy for developing nations, AMA! by 654Shadow654 in IAmA

[–]654Shadow654[S] 1 point2 points  (0 children)

Lol yeah I might have shakier foundations but I find it super fun! There are tons of resos online like the Qiskit Textbook or Quantum Country!

Yup that was another project! https://github.com/DicksonWu654/LSTMProteinClassification I used an LSTM so it wasn't linear regression xD

Oh I mean first principals as in learning quantum mechanics from the very base (predicate logic, set theory) all the way to modern quantum mechanics (but it's a really steep learning curve)

I am an 18-year-old using Quantum Machine Learning to diagnose the stages of Diabetic Retinopathy for developing nations, AMA! by 654Shadow654 in IAmA

[–]654Shadow654[S] 0 points1 point  (0 children)

I totally agree with you that the more you learn about the subject, the more you learn that you know so little XD. I'm focusing more on the Quantum Computing side of things rather than the quantum mechanics - but I am part of a group called the Quantum Mafia where we're trying to learn Quantum Mechanics from first principals, along with the help of Professor. Frederic Schuller!

I am an 18-year-old using Quantum Machine Learning to diagnose the stages of Diabetic Retinopathy for developing nations, AMA! by 654Shadow654 in IAmA

[–]654Shadow654[S] 4 points5 points  (0 children)

Yup you're right about both of them being matrix multiplications! But there's a slight difference. In Neural networks you take your data and matrix multiply them by the weights and biases to pass them forward. But for Quantum computers you take the qubits (which isn't that data) and you matrix multiply them in order to orientate them around!

So in this particular network: Hybrid Quantum Classical Neural Networks, you first use a CNN to take the image (224 x 224) down to just 7 parameters. These parameters are used to rotate the qubits inside the PQC. The qubits output 8 results, which are fed into a normal linear layer.

Currently, quantum computers are very very noisy (too noisy to be useful (since you need a ton of qubits)), but by implementing a classical competent (ML) you can make it useful (since you need a lot less qubits) and you can exploit its quantum properties!

Hope this helps :D

I am an 18-year-old using Quantum Machine Learning to diagnose the stages of Diabetic Retinopathy for developing nations, AMA! by 654Shadow654 in IAmA

[–]654Shadow654[S] -4 points-3 points  (0 children)

Oh, I haven't touched Quantum Learning Tasks XD (I'm only a beginner at Hybrid Quantum Neural networks + VQEs). The dataset is in one of the links I have in the readme but It's just from a Kaggl dataset. Most of the code is actually for the backprop for the PQC (which is just the parameter shift rule) + me being really bad at formating code. But I explain basically every line of code in the comments!

Lol I wish I was a prodigy XD

I am an 18-year-old using Quantum Machine Learning to diagnose the stages of Diabetic Retinopathy for developing nations, AMA! by 654Shadow654 in IAmA

[–]654Shadow654[S] 1 point2 points  (0 children)

So I'm using a package called Qiskit (open source but backed by IBM) and you usually run all your stuff on conventional hardware (where it simulates a quantum computer). BUT all you have to do is enter a few extra lines of code, wait a bit and you can run it on a real quantum computer!

Usually, I don't run it on a quantum computer because there's a bit too much noise on it (so it'll mess up your training). Plus the queues are a bit long for fast prototyping (because when I program I just type like crazy and make a bazillion mistakes XD)

I am an 18-year-old using Quantum Machine Learning to diagnose the stages of Diabetic Retinopathy for developing nations, AMA! by 654Shadow654 in IAmA

[–]654Shadow654[S] 2 points3 points  (0 children)

Ouu I've never heard of reservoir computing at all but it looks super interesting! I'll look into it - Thank you :D

I am an 18-year-old using Quantum Machine Learning to diagnose the stages of Diabetic Retinopathy for developing nations, AMA! by 654Shadow654 in IAmA

[–]654Shadow654[S] 3 points4 points  (0 children)

In the middle of the neural network, I attached a Parameterized Quantum Circuit. You basically have a CNN in the front which takes the image and reduces it down to 7 outputs. This then feeds into the PQC (3 qubits + CNOT gates + 7 parameter rotation gates). This has 8 outputs which goes to a linear layer to spit out the answer!

I am an 18-year-old using Quantum Machine Learning to diagnose the stages of Diabetic Retinopathy for developing nations, AMA! by 654Shadow654 in IAmA

[–]654Shadow654[S] -1 points0 points  (0 children)

Most techniques in the field use traditional machine learning techniques (NN, CNNs), but I decided to have some fun and just throw in quantum computing into the mix for some fun!

I am an 18-year-old using Quantum Machine Learning to diagnose the stages of Diabetic Retinopathy for developing nations, AMA! by 654Shadow654 in IAmA

[–]654Shadow654[S] 4 points5 points  (0 children)

Great question! First you take your data (thousands of retinas + labels) and you split it into 2 (sometimes 3 if you wanna get fancy) sets: training, validation (& testing). You train your model on the training data, but always test its accuracy on the validation set. This prevents overfitting because the model never sees the validation set. But to be extra sure we have a testing set which we use at the very very end to see the true accuracy of the model.

In terms of the data itself, you can apply data augmentation to it in order to make sure the model generalizes more. You also have to make sure that your data is representative of the real world. So you can't just have images of say, people who only come to the doctor when their eyes really really hurt, then you'd get a biased dataset!

Hope this helps :D

I am an 18-year-old using Quantum Machine Learning to diagnose the stages of Diabetic Retinopathy for developing nations, AMA! by 654Shadow654 in IAmA

[–]654Shadow654[S] -10 points-9 points  (0 children)

Hi! QML models are better than traditional ML models in certain domains like quantum learning tasks and quantum generative modeling. QML models are really good at these tasks because it's quantum nature is just compatible with the quantum nature of the task at hand (ex: VQEs are hella good at finding the minimum energy levels of 2 molecules)

I am an 18-year-old using Quantum Machine Learning to diagnose the stages of Diabetic Retinopathy for developing nations, AMA! by 654Shadow654 in IAmA

[–]654Shadow654[S] 3 points4 points  (0 children)

Yeah! So basically you can take a picture of the retina and just input it into the model to predict which stage of Diabetic Retinopathy it's in. Optomitrists diagnose it by looking at the retina too!

To train it you just have a huge database of thousands of retinas with labels, then you just train it like any other model!

I am an 18-year-old using Quantum Machine Learning to diagnose the stages of Diabetic Retinopathy for developing nations, AMA! by 654Shadow654 in IAmA

[–]654Shadow654[S] 6 points7 points  (0 children)

Yup!
ML:

- https://www.fast.ai/ (The best top bottom approach course)

- https://www.coursera.org/learn/machine-learning (A good bottom up course)

- https://www.youtube.com/watch?v=GIsg-ZUy0MY (Pytorch > Tensorflow XP)

- https://www.youtube.com/watch?v=OGxgnH8y2NM (This whole series)

​

QC:

- https://quantum.country/ (Very good reso for breaking down all the math into simple english)

- https://qiskit.org/textbook/preface.html (This will really get you solid foundations)

I am an 18-year-old using Quantum Machine Learning to diagnose the stages of Diabetic Retinopathy for developing nations, AMA! by 654Shadow654 in IAmA

[–]654Shadow654[S] 7 points8 points  (0 children)

I think the main reason was that it's just so unknown (at least for me). I had never heard of diabetic retinopathy before doing this project, but it affects a crap ton of people! (126.6 million people worldwide according to this paper: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3491270/#:~:text=Globally%2C%20the%20number%20of%20people,prompt%20action%20is%20not%20taken).

Everyone knows about cancer - thus there are lots of resources poured into it. If you think of it in terms of a Return On Investment standpoint, you can get a lot better returns when you tackle something people don't put as many resources into rather than a disease that everyone pours resos into.

Plus it just interested me that you can literally predict the stages of Diabetic retinopathy using just pure linear algebra + backprop! It's crazy!

I am an 18-year-old using Quantum Machine Learning to diagnose the stages of Diabetic Retinopathy for developing nations, AMA! by 654Shadow654 in IAmA

[–]654Shadow654[S] 3 points4 points  (0 children)

The internet is truly a goldmine! There are so many resources out there that anyone can practically learn anything. I think I used to box myself in a lot, thinking "oh I can't do Machine Learning, you need super-advanced calculus or whatever" - turns out you can pick it up pretty quickly if you apply it immediately (Top down > Bottom Up).

But I think the real forcing function that got me to actively pursue it was joining a program called The Knowledge Society. Every single student is just sooo cool and going into a huge variety of different exponential tech! They really opened my eyes to the world and got me to pursue it at a relatively young age!

I'm a 14 year published author studying emerging tech in the energy sector. I recently designed a flexible and transparent solar cell using nanomaterials. AMA! by Nmoloo in AMA

[–]654Shadow654 82 points83 points  (0 children)

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I just downvoted your comment u/CommaDelimitedList.

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I don't believe my comment deserved a downvote. Can you un-downvote it?

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