**Preface**

Machine learning, a cutting-edge branch of artificial intelligence, has made significant strides in reshaping various industries, and the field of healthcare stands at the forefront of this transformation. In this reprint of "Health and Public Health Applications for Decision Support Using Machine Learning", we delve into the dynamic and ever-evolving landscape where machine learning intersects with health sciences. This compilation brings together a diverse range of research and innovations that demonstrate the potential of data-driven algorithms to revolutionize patient care, disease diagnosis, and public health management.

Throughout this reprint, a wide array of topics and applications that exemplify the transformative power of machine learning in healthcare are explored. Researchers and healthcare professionals will find valuable insights and inspiration within these pages. Topics covered include biomedical relation extraction, blood glucose level forecasting for diabetes management, prediction of walking stability to prevent falls, automated pneumonia-infected volume quantification in CT images, heart sound classification for precision medicine, noninvasive risk assessment for early detection of renal damage, ECG measurement uncertainty analysis, smart-data-driven tools for colony-type distinction, audio-visual stress classification for mental health assessment, early diagnosis of intracranial artery stenosis using non-invasive hemodynamic indices, COVID-19 detection using multiple data modalities, and artificial intelligence models in the diagnosis of adult-onset dementia disorders.

Overall, this "Health and Public Health Applications for Decision Support Using Machine Learning" reprint explores the symbiotic relationship between machine learning and healthcare. The chapters contained herein demonstrate the breadth of possibilities that emerge when data-driven approaches are applied to medical and healthcare challenges. We hope this reprint serves as a catalyst for future research and collaboration, driving us towards a healthier and more technologically advanced future.
