ABSTRACT
Artificial intelligence (AI) is a speciality within computer science that deals with creating systems that can replicate the intelligence of a human mind and has problem-solving abilities. AI includes a diverse array of techniques and approaches such as machine learning, neural networks, natural language processing, robotics, and expert systems. An electronic literature search was conducted using the databases of "PubMed" and "Google Scholar". The period for the search was from 2000 to June 2023. The search terms included "artificial intelligence", "machine learning", "liver cancers", "liver tumors", "hepatectomy", "perioperative" and their synonyms in various combinations. The search also included all MeSH terms. The extracted articles were further reviewed in a step-wise manner for identification of relevant studies. A total of 148 articles were identified after the initial literature search. Initial review included screening of article titles for relevance and identifying duplicates. Finally, 65 articles were reviewed for this review article. The future of AI in liver cancer planning and management holds immense promise. AI-driven advancements will increasingly enable precise tumour detection, location, and characterisation through enhanced image analysis. ML algorithms will predict patient-specific treatment responses and complications, allowing for tailored therapies. Surgical robots and AI-guided procedures will enhance the precision of liver resections, reducing risks and improving outcomes. AI will also streamline patient monitoring, better hemodynamic management, enabling early detection of recurrence or complications. Moreover, AI will facilitate data-driven research, accelerating the development of novel treatments and therapies. Ultimately, AI's integration will revolutionise liver cancer care, offering personalised, efficient and effective solutions, improving patients' quality of life and survival rates.
ABSTRACT
During the past two decades, a vast number of studies done on rodents and nonhuman primates have implicated general anesthetic exposure of developing brains in producing neurotoxicity leading to various structural and functional neurological abnormalities with cognitive and behavioral deficits later in life. However, it is still unclear whether these findings translate to children and whether single exposure to anesthesia in childhood can have long-term neuro-developmental risks. Considering the fact that a large number of healthy young children are undergoing elective surgery under general anesthesia globally, any such potential neurocognitive risk of pediatric anesthesia is a serious public health issue and is therefore important to understand. This review aims to assess the current preclinical and clinical evidence related to anesthetic neurotoxicity.
