Deep learning has demonstrated remarkable accuracy analyzing images for cancer
detection tasks in recent years. The accuracy that has been achieved rivals radiologists and …

This study reviews the current status and future prospective of knowledge on the use of
artificial intelligence for the prediction of spontaneous preterm labor and birth (“preterm birth” …

To review the recent progress of machine learning for the early diagnosis of depression
(major depressive disorder). The source of data was 32 original studies in the Web of …

Brain Age (BA) estimation via Deep Learning has become a strong and reliable bio-marker
for brain health, but the black-box nature of Neural Networks does not easily allow insight …

Deep learning algorithms have recently become the dominant trend in medical image
classification. However, the decision-making rationale of convolutional neural network …

The medical imaging field needs the development of machine learning and deep learning
methods for meeting inbuilt radiological image processing complexities and to enhance the …

Machine Learning for Biomedical Applications: With Scikit-Learn and PyTorch presents
machine learning techniques most commonly used in a biomedical setting. Avoiding a …

Medical image processing is the art and science of extracting clinically meaningful
information from medical images. One exciting facet of this field is multi-modal modeling …

The medical imaging field needs the development of machine learning and deep learning
methods for meeting inbuilt radiological image processing complexities and to enhance the …

Brain Age (BA) estimation via Deep Learning has become a strong and reliable bio-marker
for brain health, but the black-box nature of Neural Networks does not easily allow insight …