- Добавил: literator
- Дата: 19-06-2024, 13:43
- Комментариев: 0
Название: The Future of Artificial Neural Networks
Автор: Indrajit Ghosal, Arun Mittal, Hemlata Jain
Издательство: Nova Science Publishers
Серия: Computer Science, Technology and Applications
Год: 2024
Страниц: 222
Язык: английский
Формат: pdf (true)
Размер: 18.0 MB
This book is a compilation of eleven quality articles exploring a variety of aspects on applications of ANN. Various authors of the articles have presented their work around the applications of ANN in healthcare and self-medication behaviour, Stock Market Analytics, ANN integrated application for industries including regulatory complaining aspect in Banking Industry, Deep Learning Framework in Medical Diagnosis, Face Recognition, Mobile Learning in Medical Education, Process and Applications of ANN using MATLAB, etc. Chapter 1 - This chapter explores the integration of Machine Learning techniques, particularly deep neural networks, in the field of medical image processing for precision medicine. The healthcare industry has accumulated vast amounts of complex data, and advancements in technology have led to an increase in structured and unstructured medical data. The chapter discusses the historical development of image processing techniques, moving from labor-intensive approaches to more efficient and faster operations using artificial neural networks. Various feature extraction methods, with a focus on dimensionality reduction, are investigated to optimize the performance of neural networks. The application of deep neural network models in medical imaging is explored, with a gradual implementation strategy proposed to address challenges related to data variability across institutions.
Автор: Indrajit Ghosal, Arun Mittal, Hemlata Jain
Издательство: Nova Science Publishers
Серия: Computer Science, Technology and Applications
Год: 2024
Страниц: 222
Язык: английский
Формат: pdf (true)
Размер: 18.0 MB
This book is a compilation of eleven quality articles exploring a variety of aspects on applications of ANN. Various authors of the articles have presented their work around the applications of ANN in healthcare and self-medication behaviour, Stock Market Analytics, ANN integrated application for industries including regulatory complaining aspect in Banking Industry, Deep Learning Framework in Medical Diagnosis, Face Recognition, Mobile Learning in Medical Education, Process and Applications of ANN using MATLAB, etc. Chapter 1 - This chapter explores the integration of Machine Learning techniques, particularly deep neural networks, in the field of medical image processing for precision medicine. The healthcare industry has accumulated vast amounts of complex data, and advancements in technology have led to an increase in structured and unstructured medical data. The chapter discusses the historical development of image processing techniques, moving from labor-intensive approaches to more efficient and faster operations using artificial neural networks. Various feature extraction methods, with a focus on dimensionality reduction, are investigated to optimize the performance of neural networks. The application of deep neural network models in medical imaging is explored, with a gradual implementation strategy proposed to address challenges related to data variability across institutions.