Sniecinski Irena, Seghatchian Jerard
Department of Transfusion Medicine, Department of Hematology and Hematopoietic Cell Transplantation, City of Hope Cancer Center, Duarte, CA, USA.
International Consultancy in Blood Components Quality/Safety improvement, Audit/Inspection, and DDR Strategies, London, UK.
Transfus Apher Sci. 2018 Jun;57(3):422-424. doi: 10.1016/j.transci.2018.05.004. Epub 2018 May 9.
Artificial Intelligence (AI) reflects the intelligence exhibited by machines and software. It is a highly desirable academic field of many current fields of studies. Leading AI researchers describe the field as "the study and design of intelligent agents". McCarthy invented this term in 1955 and defined it as "the science and engineering of making intelligent machines". The central goals of AI research are reasoning, knowledge, planning, learning, natural language processing (communication), perception and the ability to move and manipulate objects. In fact the multidisplinary AI field is considered to be rather interdisciplinary covering numerous number of sciences and professions, including computer science, psychology, linguistics, philosophy and neurosciences. The field was founded on the claim that a central intellectual property of humans, intelligence-the sapience of Homo Sapiens "can be so precisely described that a machine can be made to simulate it". This raises philosophical issues about the nature of the mind and the ethics of creating artificial beings endowed with human-like intelligence. Artificial Intelligence has been the subject of tremendous optimism but has also suffered stunning setbacks. The goal of this narrative is to review the potential use of AI approaches and their integration into pediatric cellular therapies and regenerative medicine. Emphasis is placed on recognition and application of AI techniques in the development of predictive models for personalized treatments with engineered stem cells, immune cells and regenerated tissues in adults and children. These intelligent machines could dissect the whole genome and isolate the immune particularities of individual patient's disease in a matter of minutes and create the treatment that is customized to patient's genetic specificity and immune system capability. AI techniques could be used for optimization of clinical trials of innovative stem cell and gene therapies in pediatric patients by precise planning of treatments, predicting clinical outcomes, simplifying recruitment and retention of patients, learning from input data and applying to new data, thus lowering their complexity and costs. Complementing human intelligence with machine intelligence could have an exponentially high impact on continual progress in many fields of pediatrics. However how long before we could see the real impact still remains the big question. The most pertinent question that remains to be answered therefore, is can AI effectively and accurately predict properties of newer DDR strategies? The goal of this article is to review the use of AI method for cellular therapy and regenerative medicine and emphasize its potential to further the progress in these fields of medicine.
人工智能（AI）反映了机器和软件所展现出的智能。它是当前众多研究领域中一个备受关注的学术领域。顶尖的人工智能研究人员将该领域描述为“智能体的研究与设计”。麦卡锡在1955年发明了这个术语，并将其定义为“制造智能机器的科学与工程”。人工智能研究的核心目标包括推理、知识、规划、学习、自然语言处理（通信）、感知以及移动和操纵物体的能力。事实上，多学科的人工智能领域被认为具有很强的跨学科性，涵盖了众多科学和专业领域，包括计算机科学、心理学、语言学、哲学和神经科学。该领域基于这样一种观点建立：人类的核心智力属性——智慧，即智人的智慧“能够被精确描述，从而可以制造出模拟它的机器”。这引发了关于心智本质以及创造具有类人智能的人造生物的伦理问题。人工智能一直是巨大乐观情绪的主题，但也遭遇了惊人的挫折。本文的目的是回顾人工智能方法的潜在用途及其在儿科细胞治疗和再生医学中的整合。重点在于认识和应用人工智能技术来开发针对成人和儿童的个性化治疗预测模型，这些治疗涉及工程化干细胞、免疫细胞和再生组织。这些智能机器能够在几分钟内剖析整个基因组，分离出个体患者疾病的免疫特性，并创建针对患者基因特异性和免疫系统能力定制的治疗方案。人工智能技术可用于通过精确规划治疗、预测临床结果、简化患者招募和留存、从输入数据中学习并应用于新数据，从而优化儿科患者创新干细胞和基因疗法的临床试验，降低其复杂性和成本。用机器智能补充人类智能可能会对儿科学众多领域的持续进步产生指数级的重大影响。然而，我们还要多久才能看到实际影响仍然是个大问题。因此，最亟待回答的相关问题是，人工智能能否有效且准确地预测更新的DDR策略的特性？本文的目的是回顾人工智能方法在细胞治疗和再生医学中的应用，并强调其推动这些医学领域进步的潜力。
