Artificial intelligence in Magnetic Resonance Spectroscopy

Hi all!
Artificial intelligence (AI) has achieved many accomplishments in a wide range of tasks, including the MRI field [1]. Due to the poor signal-to-noise ratio (SNR), chemical shift displacement, low spatial resolution, and overlapping of signal components of the MRS signal, AI might be a useful tool also in the MRS field. However, all known problems and challenges in AI, such as underfitting and overfitting, would also remain in the MRS domain.
This discussion thread is dedicated to the possible challenges of the application of AI in MRS.
I hope we can move it along here and this would be a great approach to converge and collaborate on some issues.
Amir M Shamaei,
[1] Alaskar, H.: Deep Learning-Based Model Architecture for Time-Frequency Images Analysis. 2019, č. January 2018.