Endoscopic Anatomy of the Skull Base.

Presently, endoscopic skull base surgery has undergone significant advancements since its inception over two decades ago. Nevertheless, it is imperative to underscore that the fundamental basis of all surgical procedures lies in the meticulous understanding of anatomy, with particular emphasis on the ventral anatomy. This facet has recently garnered increased attention.Following the advancements in endoscopic skull base surgery techniques, this chapter will concentrate on the pertinent anatomical considerations that serve as key foundations for successful procedures. These considerations are categorized into two planes: the sagittal plane and the coronal plane.The sagittal plane is further subdivided into five distinct approaches, namely,(1) the transcribriform approach, (2) the transplanum approach, (3) the transsellar approach, (4) the transclival approach, and (5) the transodontoid approach.On the other hand, the coronal plane is delineated into seven specific zones to facilitate comprehension and potential applications: (1) the petrous apex approach, (2) the intrapetrous approach, (3) the suprapetrous approach, (4) the cavernous sinus approach, (5) the infratemporal approach, (6) the medial condyle approach, and (7) the jugular foramen approach.By organizing the anatomical aspects in this systematic manner, the information provided becomes more accessible, fostering a comprehensive understanding of the subject matter for potential future application.

ChatGPT: A Conceptual Review of Applications and Utility in the Field of Medicine.

Artificial Intelligence, specifically advanced language models such as ChatGPT, have the potential to revolutionize various aspects of healthcare, medical education, and research. In this narrative review, we evaluate the myriad applications of ChatGPT in diverse healthcare domains. We discuss its potential role in clinical decision-making, exploring how it can assist physicians by providing rapid, data-driven insights for diagnosis and treatment. We review the benefits of ChatGPT in personalized patient care, particularly in geriatric care, medication management, weight loss and nutrition, and physical activity guidance. We further delve into its potential to enhance medical research, through the analysis of large datasets, and the development of novel methodologies. In the realm of medical education, we investigate the utility of ChatGPT as an information retrieval tool and personalized learning resource for medical students and professionals. There are numerous promising applications of ChatGPT that will likely induce paradigm shifts in healthcare practice, education, and research. The use of ChatGPT may come with several benefits in areas such as clinical decision making, geriatric care, medication management, weight loss and nutrition, physical fitness, scientific research, and medical education. Nevertheless, it is important to note that issues surrounding ethics, data privacy, transparency, inaccuracy, and inadequacy persist. Prior to widespread use in medicine, it is imperative to objectively evaluate the impact of ChatGPT in a real-world setting using a risk-based approach.

Artificial Intelligence in Neurosurgery: A State-of-the-Art Review from Past to Future.

In recent years, there has been a significant surge in discussions surrounding artificial intelligence (AI), along with a corresponding increase in its practical applications in various facets of everyday life, including the medical industry. Notably, even in the highly specialized realm of neurosurgery, AI has been utilized for differential diagnosis, pre-operative evaluation, and improving surgical precision. Many of these applications have begun to mitigate risks of intraoperative and postoperative complications and post-operative care. This article aims to present an overview of the principal published papers on the significant themes of tumor, spine, epilepsy, and vascular issues, wherein AI has been applied to assess its potential applications within neurosurgery. The method involved identifying high-cited seminal papers using PubMed and Google Scholar, conducting a comprehensive review of various study types, and summarizing machine learning applications to enhance understanding among clinicians for future utilization. Recent studies demonstrate that machine learning (ML) holds significant potential in neuro-oncological care, spine surgery, epilepsy management, and other neurosurgical applications. ML techniques have proven effective in tumor identification, surgical outcomes prediction, seizure outcome prediction, aneurysm prediction, and more, highlighting its broad impact and potential in improving patient management and outcomes in neurosurgery. This review will encompass the current state of research, as well as predictions for the future of AI within neurosurgery.