Interpretable machine learning: Fundamental principles and 10 grand challenges
Interpretability in machine learning (ML) is crucial for high stakes decisions and
troubleshooting. In this work, we provide fundamental principles for interpretable ML, and …
troubleshooting. In this work, we provide fundamental principles for interpretable ML, and …
Performance change with the number of training data: A case study on the binary classification of COVID-19 chest X-ray by using convolutional neural networks
K Imagawa, K Shiomoto - Computers in Biology and Medicine, 2022 - Elsevier
One of the features of artificial intelligence/machine learning-based medical devices resides
in their ability to learn from real-world data. However, obtaining a large number of training …
in their ability to learn from real-world data. However, obtaining a large number of training …
Evaluation of Effectiveness of Self-Supervised Learning in Chest X-Ray Imaging to Reduce Annotated Images
K Imagawa, K Shiomoto - Journal of Imaging Informatics in Medicine, 2024 - Springer
A significant challenge in machine learning-based medical image analysis is the scarcity of
medical images. Obtaining a large number of labeled medical images is difficult because …
medical images. Obtaining a large number of labeled medical images is difficult because …
[PDF][PDF] Interpretability and Multiplicity: a Path to Trustworthy Machine Learning
C Zhong - 2024 - dukespace.lib.duke.edu
Abstract Machine learning has been increasingly deployed for myriad high-stakes decisions
that deeply impact people's lives. This is concerning, because not every model can be …
that deeply impact people's lives. This is concerning, because not every model can be …
Performance Change with the Ratio of Training Data A Case Study on the Binary Classification of COVID-19 Chest X-Ray by using Convolutional Neural Networks
K Imagawa, K Shiomoto - 2023 IEEE International Symposium …, 2023 - ieeexplore.ieee.org
One of the features of artificial intelligence/machine learning-based medical devices resides
in their ability to learn from real-world data. The performance may change after the market …
in their ability to learn from real-world data. The performance may change after the market …