Lung Cancer Diagnosis and Treatment: An Interdisciplinary Approach - Rezaei, Nima.; SpringerLink (Online service) (Cham : Springer Nature Switzerland : Imprint: Springer, 2024)
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.
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.
Keywords: Cancer; Cancer -- Treatment; Cancer -- Animal models; Immunotherapy; Tumors -- Immunological aspects; Cancer -- Imaging; Cancer Biology; Cancer Therapy; Cancer Models; Immunotherapy; Tumour Immunology; Cancer Imaging