Machine Learning In Oncology Methods Applications And Challenges
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Artificial Intelligence for Medicine
Artificial Intelligence for Medicine: An Applied Reference for Methods and Applications introduces readers to the methodology and AI/ML algorithms as well as cutting-edge applications to medicine, such as cancer, precision medicine, critical care, personalized medicine, telemedicine, drug discovery, molecular characterization, and patient mental health. Research in medicine and tailored clinical treatment are being quickly transformed by artificial intelligence (AI) and machine learning (ML). The content in this book is tailored to the reader's needs in terms of both type and fundamentals. It covers the current ethical issues and potential developments in this field. Artificial Intelligence for Medicine is beneficial for academics, professionals in the IT industry, educators, students, and anyone else involved in the use and development of AI in the medical field. - Covers the basic concepts of Artificial Intelligence and Machine Learning, methods and practices, and advanced topics and applications to clinical and precision medicine - Presents readers with an understanding of how AI is revolutionizing medicine by demonstrating the applications of computational intelligence to the field, along with an awareness of how AI can improve upon traditional medical structures - Provides researchers, practitioners, and project stakeholders with a complete guide for applying AI techniques in their projects and solutions
Advanced Machine Learning Approaches in Cancer Prognosis
This book introduces a variety of advanced machine learning approaches covering the areas of neural networks, fuzzy logic, and hybrid intelligent systems for the determination and diagnosis of cancer. Moreover, the tactical solutions of machine learning have proved its vast range of significance and, provided novel solutions in the medical field for the diagnosis of disease. This book also explores the distinct deep learning approaches that are capable of yielding more accurate outcomes for the diagnosis of cancer. In addition to providing an overview of the emerging machine and deep learning approaches, it also enlightens an insight on how to evaluate the efficiency and appropriateness of such techniques and analysis of cancer data used in the cancer diagnosis. Therefore, this book focuses on the recent advancements in the machine learning and deep learning approaches used in the diagnosis of different types of cancer along with their research challenges and future directions for the targeted audience including scientists, experts, Ph.D. students, postdocs, and anyone interested in the subjects discussed.
Novel methods and technologies for the evaluation of drug outcomes and policies
Author: Zaheer-Ud-Din Babar
language: en
Publisher: Frontiers Media SA
Release Date: 2024-04-10
As a leading Open Access publisher, Frontiers is committed to empowering not only scientists, but other researchers, innovators and members of the public. As such, highlighting sustainable development and the real-world applications of Drugs Outcomes Research & Policies are a key part to the agenda of Frontiers in Pharmacology. This Research Topic aims to highlight advancements in Health Economics and Outcomes Research (HEOR) techniques, methods and tools used by the pharmaceutical industry and other non-academic bodies.