Artificial Intelligence is revolutionizing the field of neurology and neurosurgery by enhancing diagnostic accuracy, treatment planning, and surgical precision. AI-powered algorithms analyze complex neuroimaging data to detect subtle patterns, enabling earlier identification of conditions like stroke, brain tumors, and neurodegenerative diseases. In the realm of artificial intelligence in neurology and neurosurgery, AI integrates with robotics to optimize precision during surgical procedures, reducing risks and improving patient outcomes. Machine learning models further contribute by predicting patient responses to therapies, facilitating more personalized treatment strategies. The continuous integration of AI in neurological research and practice is driving innovation, offering transformative solutions to the complex challenges associated with brain and nervous system care.
Title : Perception and individuality in patient cases identifying the ongoing evolution of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS)
Ken Ware, NeuroPhysics Therapy Institute, Australia
Title : Narrative medicine: A communication therapy for the communication disorder of Functional Seizures (FS) [also known as Psychogenic Non-Epileptic Seizures (PNES)]
Robert B Slocum, University of Kentucky HealthCare, United States
Title : Personalized and Precision Medicine (PPM), as a unique healthcare model through biodesign-driven biotech and biopharma, translational applications, and neurology-related biomarketing to secure human healthcare and biosafety
Sergey Victorovich Suchkov, N. D. Zelinskii Institute for Organic Chemistry of the Russian Academy of Sciences, Russian Federation
Title : Neuro sensorium
Luiz Moutinho, University of Suffolk, United Kingdom
Title : GBF1 inhibition reduces amyloid-beta levels in viable human postmortem Alzheimer's disease cortical explant and cortical organoid models
Sean J Miller, Yale School of Medicine, United States
Title : Traumatic Spinal Cord Injuries (tSCI) - Are the radiologically based “advances” in the management of the injured spine evidence-based?
W S El Masri, Keele University, United Kingdom