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Medical diagnosis systems based on artificial neural networks

Are there any medical diagnosis systems that are already used somewhere that are based on artificial neural networks?
vojtak
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7
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What is the difference between artificial intelligence and cognitive science?

Sometimes I understand that people doing cognitive science try to avoid the term artificial intelligence. The feeling I get is that there is a need to put some distance to the GOFAI. Another impression that I get is that cognitive science is more…
Luis
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Why is the state-action value function used more than the state value function?

In reinforcement learning, the state-action value function seems to be used more than the state value function. Why is it so?
7
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How can the theory of multiple intelligences be incorporated into AI?

I have been wondering since a while ago about the theory of multiple intelligences and how they could fit in the field of Artificial Intelligence as a whole. We hear from time to time about Leonardo Da Vinci being a genius or Bach's musical…
Luis
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7
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How to estimate the capacity of a neural network?

Is it possible to estimate the capacity of a neural network model? If so, what are the techniques involved?
7
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Are PAC learnability and the No Free Lunch theorem contradictory?

I am reading the Understanding Machine Learning book by Shalev-Shwartz and Ben-David and based on the definitions of PAC learnability and No Free Lunch Theorem, and my understanding of them it seems like they contradict themselves. I know this is…
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Why do ResNets avoid the vanishing gradient problem?

I read that, if we use the sigmoid or hyperbolic tangent activation functions in deep neural networks, we can have some problems with the vanishing of the gradient, and this is visible by the shapes of the derivative of these functions. ReLU solves…
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Why does reinforcement learning using a non-linear function approximator diverge when using strongly correlated data as input?

While reading the DQN paper, I found that randomly selecting and learning samples reduced divergence in RL using a non-linear function approximator (e.g a neural network). So, why does Reinforcement Learning using a non-linear function approximator…
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When training a CNN, what are the hyperparameters to tune first?

I am training a convolutional neural network for object detection. Apart from the learning rate, what are the other hyperparameters that I should tune? And in what order of importance? Besides, I read that doing a grid search for hyperparameters is…
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How good is AI at generating new, unseen [visual] examples?

By new, unseen examples; I mean like the animals in No Man's Sky. A couple of images of the animals are: So, upon playing this game, I was curious about how good is AI at generating visual characters or examples?
Dawny33
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Is Sanskrit still relevant for NLP/AI?

I came across a news article from 2018 where the president of India was saying that Sanskrit is the best language for ML/AI. I have no idea regarding his qualification on either AI or Sanskrit to say this but this idea has been floated earlier in…
Borun Chowdhury
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Can training a model on a dataset composed by real images and drawings hurt the training process of a real-world application model?

I'm training a multi-label classifier that's supposed to be tested on underwater images. I'm wondering if feeding the model drawings of a certain class plus real images can affect the results badly. Was there a study on this? Or are there any past…
user
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How to classify human actions?

I'm quite new to machine learning (I followed the Coursera course of Andrew Ng and now starting deeplearning.ai courses). I want to classify human actions real-time like: Left-arm bended Arm above shoulder ... I first did some research for…
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How to use BERT as a multi-purpose conversational AI?

I'm looking to make an NLP model that can achieve a dual purpose. One purpose is that it can hold interesting conversations (conversational AI), and another being that it can do intent classification and even accomplish the classified task. To…
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When exactly is a model considered over-parameterized?

When exactly is a model considered over-parameterized? There are some recent researches in Deep Learning about the role of over-parameterization toward generalization, so it would be nice if I can know what exactly can be considered as such. A…