Cancer is a leading cause of death worldwide, according to WHO. Currently the primary treatments available for it, that include chemotherapy and radiotherapy, have several side-effects. Much new research is being done in its diagnosis and treatment with less invasive techniques. Artificial intelligence, bioimpedance, thermal images and nanomaterials have been studied to provide early diagnosis. New treatments based on the generation of microwaves, radiofrequency or ultrasound have been proposed in the last couple of decades.

Although thermotherapies have proved to be efficient, for it to be considered as a primary treatment, it needs to overcome some hurdles. One of the main challenges is to ensure applicators that point the electromagnetic or the mechanical waves at a tissue, don't affect the surrounding healthy tissues. In some cases, nanoparticles have also been designed to achieve better focus. The design of new applicators can be made by computational models based on methods such as the finite element. However, to efficiently predict the applicator performance, it is important to that dielectric, thermal and acoustic properties (tissue characterization) are included in the models. Not only healthy tissue but also tumors must be characterized. A powerful tool called patient specific treatment planning can be developed to implement a safety treatment which consists of a 3D patient model based on medical images. Moreover, tissue properties as well as the applicator must be defined. Parameters such as temperature increase, and heat pattern must be evaluated to ensure patient safety and treatment success.

This book discusses the latest trends in the subject, such as artificial intelligence, thermal images, bioimpedance to diagnose cancer, and novel treatment techniques. Moreover, the role of thermal therapy as a new cancer treatment capable of reducing side effects in patients has been reviewed. Key topics from the engineering and medical point of view to implement a successful treatment (hyperthermia/ablation) by using radiofrequency, microwaves, ultrasound, or nanoparticles (magneto hyperthermia) are addressed. The target audience includes biomedical, electrical, and computational engineering, health professionals, medical doctors, practitioners, and students.

Citlalli Jessica Trujillo-Romero was born in Mexico City in 1983. She holds a bachelor's degree in Bionic Engineering from the National Polytechnic Institute (IPN) in 2006, a Ph.D. degree at the Bioelectronics Section of the Electrical Engineering Department at CINVESTAV-IPN in 2012. She did two doctoral stays, the first one at the Center for Research in Automatica, in Nancy, France (CRAN-INPL) and the second at the Hyperthermia Unit, in the Department of Radiation Oncology, at the Erasmus MC, Rotterdam, the Netherlands. Dr. Trujillo-Romero worked as a postdoc at the Oncological Radiation Department, Hyperthermia Unit at the Erasmus MC Daniel den Hoed in Rotterdam, Netherland from 2012-2014. She worked as a full-time professor at the National Polytechnic Institute (IPN) in 2015. She was a part time professor at the Monterrey Institute of Technology and Higher Education (ITESM) from 2015-2019. Since 2016, Dr. Trujillo-Romero is a Scientific Research Advisor at Machina Innovation Lab, a company specializes in building start-ups for the commercialization of new products and services, based on the assimilation of scientific and technological advances. Currently, she works as a researcher in medical science at the National Institute of Rehabilitation-LGII in Mexico City. She has 14 peer reviewed manuscripts, 1 book chapter and two patents; she has more than 30 conference proceedings. She is associate editor in Revista Mexicana de Ingeniería Biomédica and active member of the Mexican Society of Biomedical Engineering (SOMIB). She has won several awards including the National System of Research recognition and the first place in the Health Innovation Award in the INC Discovery category. This award aims to stimulate entrepreneurship in health and promote young talent in Mexico and Latin America (2019). She has been participated in several projects, as a Leader and associated researcher, related to the use of thermo therapies to treat cancer and pain. Her main field of study is the use of electromagnetic fields, microwaves and ultrasound to generate thermal therapies to treat tumors by hyperthermia and thermal ablation, as well as to treat pain. Moreover, she is interested in the development of computational models and medical devices.

Dora-Luz Flores is Associate Professor in the Facultad de Ingeniería, Arquitectura y Diseño at the Universidad Autónoma de Baja California. She received her MS from Instituto Politécnico Nacional and her PhD from Universidad Autónoma de Baja California and did a research stay at the University of California Irvine, in the Department of Biomedical Engineering. Dr. Flores received the Fulbright-Garcia Robles Fellowship and has won several awards including the National System of Researchers recognition, PRODEP recognition, Merit Graduate School Award, and Merit Undergraduate School Award. Also, Prof. Flores is member of the Liaison Committee of the International Science Council Regional Focal Point for the Latin American and Caribbean Region. She has coauthored over 40 peer reviewed manuscripts and 5 book chapters, is Editor-in-chief in Revista Mexicana de Ingeniería Biomédica, has served as a reviewer over 15 peer reviewed manuscripts, and has organized 18 national/international conferences. Her current research interest focuses on machine learning and artificial intelligence applied to biological systems. Specifically, using statistical methods for learning from data, including data mining in bioengineering, computational biology, and design of experiments of nanomaterials. Her core competences are in the fields of machine learning and artificial intelligence such as Genetic Algorithms, Artificial Neural Networks, Support Vector Machines, Fuzzy Logic, Agents and Multi Agent Systems applied to biological systems (marine species, biomedicine) and nanomaterials (luminescent) to create computational models to predict or classify, using programming languages and computational tools such as Python, Matlab, R programming, Java, C, NetLogo, Weka, Meka. In addition to research and teaching, Dr. Flores is passionate about diversity and community initiatives. Her objectives are to continue with a solid, collaborative, and productive laboratory committed to the growth and development of its research group through specific teaching, mentoring, and assistance in the university's strategic growth through service, increasing diversity, and collaboration.