Sami Trop Data Set and Classification Clarification

[Mohammed Syed]

Greetings

I apologize in advance if this question has been answered before.

The tensor size for SamiTrop data is 4096 x 12 for each sample. 

Question:

Does the model need to classify a sample of this size (4096 x 12)?

In other words, do we need to classify each feature (of 12 total leads) separately?

(or) the model needs to classify each individual feature/ lead separately?

Many thanks 

[PhysioNet Challenge]

Dear Mohammed,

The Challenge data come from different sources. These data sources have different numbers of records, different sampling frequencies, different numbers of samples, and, importantly, different file formats, among other differences. To make it easier for your code to run on data from different sources, including new data sources, we convert the data from each source to WFDB format, and we run your code on the WFDB versions of the data.

In particular, you should not expect the file format from the SaMiTrop data, and your code will not have access to it. You should not expect that each record will have 4096 samples. You can decide whether to use each lead separately or all of the leads together.

Please see these instructions and commands for how to prepare the public training data for the Challenge; we will prepare the hidden validation and test data, which are from different sources, very similarly:
https://github.com/physionetchallenges/python-example-2025?tab=readme-ov-file#how-do-i-create-data-for-these-scripts

Please also run the example and scoring code to understand how the data are formatted and will be used by your code.
https://github.com/physionetchallenges/matlab-example-2025
https://github.com/physionetchallenges/python-example-2025
https://github.com/physionetchallenges/evaluation-2025

Best,
Matt
(On behalf of the Challenge team.)

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