Greetings everyone,
I am working on a software as medical device that has a machine learning component to it (eg. Tensorflow model). In short, it is an image processing application that evaluates the volume of anatomical structures from medical scans to assist diagnosis.
I'm currently following IEC62304 for the "model code" (model weights + inference code), however I'm having a hard time finding information on how I should treat the "training code" (dataset management, model fitting, model evaluation), since it is not part of the SaMD per say.
I've read in a Johner-Institute blog post on machine learning that the "training code" should satisfy ISO-13485:2016 requirements regarding "computerized system validation" (GAMP5-Category 5). I'm assuming that it refers to section 7.5.6 (Validation of processes for production and service provision), however that section also state that it applies to processes "where the resulting output cannot be verified by subsequent monitoring or measurement [...]". In my case, I can still evaluate the performances of the machine learning component independently of the "training code".
Do you have any thoughts on this ? Any experience/strategy regarding ML and SaMD?
I am working on a software as medical device that has a machine learning component to it (eg. Tensorflow model). In short, it is an image processing application that evaluates the volume of anatomical structures from medical scans to assist diagnosis.
I'm currently following IEC62304 for the "model code" (model weights + inference code), however I'm having a hard time finding information on how I should treat the "training code" (dataset management, model fitting, model evaluation), since it is not part of the SaMD per say.
I've read in a Johner-Institute blog post on machine learning that the "training code" should satisfy ISO-13485:2016 requirements regarding "computerized system validation" (GAMP5-Category 5). I'm assuming that it refers to section 7.5.6 (Validation of processes for production and service provision), however that section also state that it applies to processes "where the resulting output cannot be verified by subsequent monitoring or measurement [...]". In my case, I can still evaluate the performances of the machine learning component independently of the "training code".
Do you have any thoughts on this ? Any experience/strategy regarding ML and SaMD?
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