Artificial Intelligence Application in Health Care System

Dear Colleagues,

Machine learning, a hot research topic with a huge amount of recent progress, brings dramatic changes and improvement in health care systems. Famously, a deep learning model (a convolutional neural network) halved the second best error rate on the image classification task in the ImageNet Large-Scale Visual Recognition Challenge (ILSVRC) in 2012. These breakthroughs are attributed to the easily accessible and annotated data and the explosion of the available computing power, enabling the use of neural networks, which are deeper than before. Nowadays, these models form state-of-the-art approaches to various problems in computer vision, language modeling, and signal processing. Health care providers obtain enormous amounts of data containing extremely valuable signals and information. Therefore, machine learning has rapidly entered the biomedical research field to integrate, analyze, and make predictions based on large and heterogeneous datasets. In this Special Issue, we would like to explore "Artificial Intelligence Applications in Health Care Systems", which often involves a training set for fitting models, a validation set for hyperparameter selections, and a test set for performance assessment. A validation set could be ignored if there is no hyperparameter selection process, and performance assessment can be conducted based on k-fold cross-validation. Studies following the above criteria with potential impacts on real clinical practice based on artificial intelligence-assisted systems are considered for publication in the Special Issue titled "Artificial Intelligence Applications in Health Care Systems" in the Journal of Personalized Medicine (IF: 3.508, ISSN 2075-4426).  We appreciate your research and look forward to hearing from you.

Dr. Chin-Sheng Lin
Dr. Chin Lin
Dr. Hung-Yu Wei
Guest Editors

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