@article{1438119,
      recid = {1438119},
      author = {Elloumi, Mourad,},
      title = {Deep learning for biomedical data analysis : techniques,  approaches, and applications /},
      pages = {1 online resource :},
      note = {Includes index.},
      abstract = {This book is the first overview on Deep Learning (DL) for  biomedical data analysis. It surveys the most recent  techniques and approaches in this field, with both a broad  coverage and enough depth to be of practical use to working  professionals. This book offers enough fundamental and  technical information on these techniques, approaches and  the related problems without overcrowding the reader's  head. It presents the results of the latest investigations  in the field of DL for biomedical data analysis. The  techniques and approaches presented in this book deal with  the most important and/or the newest topics encountered in  this field. They combine fundamental theory of Artificial  Intelligence (AI), Machine Learning (ML) and DL with  practical applications in Biology and Medicine. Certainly,  the list of topics covered in this book is not exhaustive  but these topics will shed light on the implications of the  presented techniques and approaches on other topics in  biomedical data analysis. The book finds a balance between  theoretical and practical coverage of a wide range of  issues in the field of biomedical data analysis, thanks to  DL. The few published books on DL for biomedical data  analysis either focus on specific topics or lack technical  depth. The chapters presented in this book were selected  for quality and relevance. The book also presents  experiments that provide qualitative and quantitative  overviews in the field of biomedical data analysis. The  reader will require some familiarity with AI, ML and DL and  will learn about techniques and approaches that deal with  the most important and/or the newest topics encountered in  the field of DL for biomedical data analysis. He/she will  discover both the fundamentals behind DL techniques and  approaches, and their applications on biomedical data. This  book can also serve as a reference book for graduate  courses in Bioinformatics, AI, ML and DL. The book aims not  only at professional researchers and practitioners but also  graduate students, senior undergraduate students and young  researchers. This book will certainly show the way to new  techniques and approaches to make new discoveries.},
      url = {http://library.usi.edu/record/1438119},
      doi = {https://doi.org/10.1007/978-3-030-71676-9},
}