肿瘤领域的人工智能和精准医学

Ojaswini Singh, Rishabh Singh, Ankur Saxena
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引用次数: 1

摘要

人工智能可以帮助加速对大量数据的分析过程,在数据中锚定模式,从而更快地做出建议性决策。复杂的先见之明模型是通过从数据中提取模式并预测结果的算法产生的。人工智能分为人工狭义智能(ANI)、人工通用智能(AGI)和人工超级智能(ASI)三个阶段。精准医学是一种新兴的疾病预防和治疗方法,基于特定的遗传、环境条件和个体患者的生活方式选择。人工智能算法已被发现在简化恶性生长筛选和发现方面具有引人注目的作用。人工智能框架能够识别单一的药物反应变异性,根据从大量公开和独家信息中学习到的模式提出建议,并有助于扩大精准医学的前沿,特别是癌症基因组学。
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Artificial Intelligence And Precision Medicine For Oncology
AI can help to essentially accelerate the process of analysis of vast amounts of data, anchoring patterns in the data, resulting in faster and recommended decision-making. Sophisticated prescient models are produced using algorithms that extract the patterns from data and predict results. AI is categorized into three stages namely, artificial narrow intelligence (ANI), artificial general intelligence(AGI), and artificial super intelligence(ASI). Precision medicine is a rising methodology for disease prevention and treatment based on the specific hereditary, environment conditions, and lifestyle choices of an individual patient. AI algorithms have been found to be compelling in streamlining malignant growth screening and discovery. AI frameworks are able to recognize singular drug-response variability, making recommendations based on patterns learned from vast amounts of public and exclusive information, and can help expand the frontier of precision medicine, specially of cancer genomics.
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