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The most recent developments in diagnostic and therapeutic aspects of Gliomas (glioblastoma) in the brain are presented.  The importance of personalized medicine and clinical validation for targeted therapy are discussed. The identification of various types of biomarkers (determined by molecular genetics) is included, along with their advantages and limitations as markers in tumor detection and diagnosis. The identification and validation of brain cancer (glioblastoma) genes are discussed. The role of cancer stem cells in the initiation and persistence of malignant gliomas is explained; response of glioblastoma cancer stem cells to various growth factors, such as epidermal growth factor receptor kinase inhibitor, is explained. The use of surgical resection, chemotherapy (e.g., temozolomide), immunotherapy, and radiation therapy for glioblastoma patients is included. Biological impediments for chemotherapy and radiotherapy for malignant glioblastoma are pointed out. Standard (established) as well as newer imaging modalities (proton magnetic resonance spectroscopy) are discussed. Also included are proton magnetic resonance spectroscopy in intracranial gliomas, and the use of proton magnetic spectroscopic imaging in determining the infiltration zone in gliomas. The role of molecular signaling in the CNS cancer development is explained, including cell death signaling in glioblastoma multiforme.

Brain -- Tumors -- Diagnosis. --- Brain -- Tumors -- Treatment. --- Neuroradiology. --- Neurosurgery. --- Glioma --- Nervous System Neoplasms --- Hemangioma, Capillary --- Neoplasms, Neuroepithelial --- Hemangioma --- Nervous System Diseases --- Neoplasms by Site --- Neuroectodermal Tumors --- Neoplasms, Glandular and Epithelial --- Diseases --- Neoplasms --- Neoplasms, Vascular Tissue --- Neoplasms, Nerve Tissue --- Neoplasms, Germ Cell and Embryonal --- Neoplasms by Histologic Type --- Ganglioglioma --- Astrocytoma --- Hemangioblastoma --- Central Nervous System Neoplasms --- Medicine --- Health & Biological Sciences --- Oncology --- Central nervous system --- Astrocytomas. --- Tumors. --- Astrocytes --- Astrocytic gliomas --- Astrogliomas --- Astromas --- Cancer --- Tumors --- Medicine. --- Cancer research. --- Oncology. --- Pathology. --- Surgery. --- Biomedicine. --- Cancer Research. --- Gliomas --- Radiology, Medical. --- Oncology  . --- Surgery, Primitive --- Nerves --- Neurosurgery --- Clinical radiology --- Radiology, Medical --- Radiology (Medicine) --- Medical physics --- Disease (Pathology) --- Medical sciences --- Medicine, Preventive --- Surgery --- Neuroradiography --- Neuroradiology --- Nervous system --- Cancer research

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This book focuses on a variety of interdisciplinary perspectives concerning the theory and application of artificial intelligence (AI) in medicine, medically oriented human biology, and healthcare. The list of topics includes the application of AI in biomedicine and clinical medicine, machine learning-based decision support, robotic surgery, data analytics and mining, laboratory information systems, and usage of AI in medical education. Special attention is given to the practical aspect of a study. Hence, the inclusion of a clinical assessment of the usefulness and potential impact of the submitted work is strongly highlighted.

Technology: general issues --- History of engineering & technology --- computational intelligence --- medical assistance --- instance-based learning --- healthcare --- clinical decision support systems --- deep neural networks --- medical imaging --- backdoor attacks --- security and privacy --- COVID-19 --- gastric cancer --- endoscopy --- deep learning --- convolutional neural network --- brain --- pituitary adenoma --- dysembryoplastic neuroepithelial tumor --- DNET --- ganglioglioma --- digital pathology --- computer vision --- machine learning --- CNN --- ATLAS --- HarDNet --- Swin transformer --- segmentation --- U-Net --- cerebral infarction --- CycleGAN --- advanced statistics --- schizophrenia --- aggression --- forensic psychiatry --- medical image segmentation --- CT image segmentation --- kernel density --- semi-automated labeling tool --- Bayesian learning --- neuroimaging --- feature selection --- kernel formulation --- mental disorders --- MRI --- visual acuity --- fundus images --- ophthalmology --- SVM --- computational intelligence --- medical assistance --- instance-based learning --- healthcare --- clinical decision support systems --- deep neural networks --- medical imaging --- backdoor attacks --- security and privacy --- COVID-19 --- gastric cancer --- endoscopy --- deep learning --- convolutional neural network --- brain --- pituitary adenoma --- dysembryoplastic neuroepithelial tumor --- DNET --- ganglioglioma --- digital pathology --- computer vision --- machine learning --- CNN --- ATLAS --- HarDNet --- Swin transformer --- segmentation --- U-Net --- cerebral infarction --- CycleGAN --- advanced statistics --- schizophrenia --- aggression --- forensic psychiatry --- medical image segmentation --- CT image segmentation --- kernel density --- semi-automated labeling tool --- Bayesian learning --- neuroimaging --- feature selection --- kernel formulation --- mental disorders --- MRI --- visual acuity --- fundus images --- ophthalmology --- SVM