How to classify my 1 dimensional data with 1D cnn?

I have a biomedical dataset of cancer classification, the data has a very high dimension, but it’s 1 dimension for each data, so for every case, we will have 1*N features, inthis case, N is 1999.

The data kinda looks something like this

[positive, N[1], N[2], N[3], … [N1999]]

there are 62 case for this colon cancer dataset, and 40 are negatives, 22 positives.

Any guidance or direction I should take to tackle this problem?

I would love to use 1D cnn since I’ve used 2D CNN in image classification before, but wondering if this is applicable

Is there any VGG or Resnet equivalent for 1D convolution?

I don’t think there are pretrained models available for 1D CNN.

Maybe you should try some machine learning approaches like CatBoost. As this problem is simply a classification problem with give N features which is hetrogenous data and Deep learning in general is good for homogenous data like images, audio, text.