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ramp-kits / autism

Data Challenge on Autism Spectrum Disorder detection
https://paris-saclay-cds.github.io/autism_challenge/
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Information on fMRI acquisition #36

Open SRSteinkamp opened 6 years ago

SRSteinkamp commented 6 years ago

Dear all,

first of all thanks for organizing the challenge, it's a blast getting started with this :)

I was looking into creating features from the resting state data (not necessarily based on functional connectivity) and saw that the time series are of different length. Which is in a clinical setting with different sites definitely understandable.

However, now I am wondering whether the data was acquired using the same BOLD sequences. Or whether there are some information on acquisition parameters. Especially the TR, which would be necessary / useful for applying some temporal filtering on the data or using temporal features.

Best, Simon

(I hope I just didn't overlook the info somewhere...)

glemaitre commented 6 years ago

It is true that those metadata would be useful. However, we will not be able to provide them for the running challenge.

GaelVaroquaux commented 6 years ago

I am with Guillaume right now, and he wants to moderate his answer: he will try to provide the TR, but makes no promises.

glemaitre commented 6 years ago

Ok, so the TR information should be available by tomorrow. We need to synchronize the autism kit (#39) as well as the different data set to make sure of not breakdown in the submission process.

glemaitre commented 6 years ago

The feature is now available in the last commit of this repository. You can access the TR data as:

In [1]: from problem import get_train_data

In [2]: X, y = get_train_data()

In [3]: X['repetition_time']
Out[3]: 
subject_id
1932355398536124106     2.50000
5174041730092253771     3.00000
10219322676643534800    3.00000
10645466564919190227    2.50000
...
7789126193351344754     2.00000
9057622900394015793     2.00000
10099127552657342413    2.00000
Name: repetition_time, Length: 1127, dtype: float64
SRSteinkamp commented 6 years ago

Thank you so much :) ... I really appreciate it, as I always feel a little guilty, when a quick question like this results in so much work for you guys.

Let's see how this can be put to use!