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Lung Cancer Diagnosis and Treatment: An Interdisciplinary Approach -

Lung Cancer Diagnosis and Treatment: An Interdisciplinary Approach

Nima Rezaei (Herausgeber)

Buch | Hardcover
XI, 364 Seiten
2024
Springer International Publishing (Verlag)
978-3-031-74328-3 (ISBN)
CHF 299,55 inkl. MwSt
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The "Lung Cancer Diagnosis and Treatment: An Interdisciplinary Approach" is the ninth volume of the "Interdisciplinary Cancer Research" series, publishes comprehensive reviews on the diagnosis and treatment of lung cancer. Application of artificial intelligence in lung cancer detection is explained well. Recent advances in the treatment of lung cancer is presented in this volume, while opportunities and challenges in immunotherapy are discussed. This interdisciplinary series is of special value to researchers working on oncology. This is the main concept of Cancer Immunology Project (CIP), which is a part of Universal Scientific Education and Research Network (USERN). This interdisciplinary book will be of special value to researchers, oncologists, and oncosurgeons who wish to extend their knowledge on lung cancer.

Professor Nima Rezaei gained his medical degree (MD) from Tehran University of Medical Sciences and subsequently obtained an MSc in Molecular and Genetic Medicine and a PhD in Clinical Immunology and Human Genetics from the University of Sheffield, UK. He also spent a short-term fellowship of Pediatric Clinical Immunology and Bone Marrow Transplantation in the Newcastle General Hospital.  Prof. Rezaei is now the Full Professor of Immunology and Vice Dean of Research and Technologies, School of Medicine, Tehran University of Medical Sciences, and the co-founder and Head of the Research Center for Immunodeficiencies. He is also the Founder of Universal Scientific Education and Research Network (USERN). Prof. Rezaei has already been the Director of more than two hundred research projects and has designed and participated in several international collaborative projects. Prof. Rezaei is the editor, editorial assistant, or editorial board member of more than fifty international journals. He has edited more than one hundred international books, has presented more than a thousand lectures/posters in congresses/meetings, and has published more than 1,500 scientific papers in the international journals.

Application of Artificial Intelligence in Lung Cancer Detection: The Integration of Computational Power and Clinical Decision-Making.- Advancement in Lung Cancer Diagnosis: A Comprehensive Review of Deep Learning Approaches.- AI Role to Decipher High-Dimensional Data for Early Prognosis of Non-Small-Cell Lung Cancer.- Emerging Paradigms in Lung Cancer Treatment: Recent Breakthroughs and Innovation.- Targeting Immune Determinants of Creating Tumor Heterogeneity in Lung Cancer.- Checkpoint Inhibitors in Non-small Cell Lung Cancer: Potentials and Challenges.- Nanoparticles: A Treatment Modality for Lung Cancer.- Applications of Metallic Nanoparticles in Lung Cancer Treatment.- Combination of Stereotactic Ablative Radiotherapy and Systemic Therapy in Oligoprogressive Non-small Cell Lung Cancer.- Challenges in First-Line Osimertinib Therapy in EGFR-Mutant Non-small Cell Lung Cancer: Acquired Resistance Is the Issue.- Lung Immunotherapy in the Elderly with NSCLC - the Who, the What, and the When.- Drug Resistance in Lung Cancer.- Patient-Derived Organoids as a Stem Cell Model to Study Lung Cancer.- The Multidisciplinary Management of Lung Cancer in the European Community.

Erscheinungsdatum
Reihe/Serie Interdisciplinary Cancer Research
Zusatzinfo XI, 364 p. 37 illus., 34 illus. in color.
Verlagsort Cham
Sprache englisch
Maße 155 x 235 mm
Themenwelt Medizin / Pharmazie Medizinische Fachgebiete Onkologie
Studium Querschnittsbereiche Infektiologie / Immunologie
Schlagworte Artificial Intelligence • cancer diagnosis • Cancer Management • Cancer Treatment • drug resistance • immunotherapy • nanoparticles • Patient-derived organoids • radiotherapy • Stem Cell
ISBN-10 3-031-74328-8 / 3031743288
ISBN-13 978-3-031-74328-3 / 9783031743283
Zustand Neuware
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