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Home > Digital Pathology Podcast > Top 5 Mistakes you must AVOID in using Machine Learning for pathology w/ Heather Couture, PixelScientia Labs
Podcast: Digital Pathology Podcast
Episode:

Top 5 Mistakes you must AVOID in using Machine Learning for pathology w/ Heather Couture, PixelScientia Labs
Category: Science & Medicine
Duration: 00:32:20
Publish Date: 2023-03-22 02:00:00
Description:

The field of pathology has been revolutionized by the introduction of machine learning techniques, which enable more efficient and accurate diagnoses and have the potential to some day even eliminate or reduce the number of expensive molecular tests. However, the model development is a complex process and  there are certain mistakes that must be avoided when using machine learning for pathology. 

In this informative discussion with Heather Couture, an expert in machine learning for pathology, she highlights the top 5 MISTAKES THAT YOU MUSTAVOID to ensure the best possible machine learning and deep learning project outcomes.

Through her insights, you will learn about the importance of:

  1. selecting the right data, 
  2. avoiding bias in data collection, 
  3. ensuring proper preprocessing of data, 
  4. choosing the right model, and 
  5. monitoring model performance. 


By avoiding these common mistakes, you can maximize the benefits of machine learning for pathology and ensure accurate and timely project results and product launches. Whether you are new to machine learning or an experienced practitioner, this discussion is a valuable resource for anyone interested in using machine learning (including deep learning) for pathology.

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