دانلود کتاب یادگیری عمیق برای تصمیم گیری مراقبت های بهداشتی

Healthcare today is known to suffer from siloed and fragmented data delayed clinical communications and disparate workflow tools due to the lack of interoperability caused by vendor-locked healthcare systems, lack of trust relationships among data holders, and security/privacy concerns regarding data sharing. The present generation and scenario are a time for big leaps and bounds in terms of growth and advancement of the health information industry. This book is an attempt to unveil the hidden potential of the vast health information and technology. Through this book, we attempt to combine numerous compelling views, guidelines, and frameworks on enabling personalized healthcare service options through the successful application of deep learning frameworks. The progress of the healthcare sector shall be incremental as it learns from associations between data over time through the application of suitable artificial intelligence, deep net frameworks, and patterns. The major challenge healthcare is facing is the effective and accurate learning of unstructured clinical data through the application of precise algorithms. Incorrect input data leading to erroneous outputs with false positives shall be intolerable in healthcare as patients’ lives are at stake. This book is being formulated with the intent to uncover the stakes and possibilities involved in realizing personalized healthcare services through efficient and effective deep learning algorithms.

The specific focus of this book will be on the application of deep learning in any area of healthcare, including clinical trials, telemedicine, health records management, etc. For the book, we are seeking articles that focus on the intersection of deep learning, healthcare, and computer engineering approaches. The book is divided into five sections: Section 1 is deep learning in healthcare; chapters 1 and 2 fall under this category. Section 2 is deep learning in diagnosis and image analysis; chapters 3–5 fall under this section. Section 3 is deep learning in medical and healthcare records; chapters 6–8 fall under this section. Section 4 is deep learning applications in COVID; chapters 10 and 11 fall under this category. Section 5 is deep learning in healthcare cybersecurity and blockchain; chapters 11–13 fall under this section.