癌症:人工智能可以治愈的计算疾病Cancer: A Computational Disease that AI Can Cure |
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课程网址: | http://videolectures.net/aaai2010_tenenbaum_cac/ |
主讲教师: | Jay M. Tenenbaum |
开课单位: | Collabrx公司 |
开课时间: | 2010-09-01 |
课程语种: | 英语 |
中文简介: | **罗伯特·s·恩格尔莫尔纪念奖演讲** -癌症是由有限的基因突变引起的,生物技术可以很容易地列出这些基因突变,我们可以从生物化学的基础上理解和推理这些基因突变。可悲的是,科学界和医学界正在使用一种非常低效的非适应性策略来寻找治疗方法,在这种策略中,实验的成本是用生命和金钱来衡量的,而我们只获取了一小部分基因组学和结果数据,即在美国,这一研究结果在临床试验中得到了证实。受我作为人工智能研究人员、互联网企业家和癌症幸存者的职业经历的启发,我正试图通过“癌症公地”(cancer Commons)来纠正这种情况。病人,医生和研究人员的社区。我们的目标是治愈癌症通过收集从成千上万的基因和响应数据adaptively-planned个体治疗实验,结合产生的稀疏的碎片证据推断肿瘤和真正的因果机制的药物,和推广得到的知识可以应用于新病例。每个病人都是按照现有的最佳知识接受治疗的,这些知识会不断更新,以造福下一个病人。希望这种自适应的方法能够有效地爬坡找到治愈癌症的方法,一次一个病人 |
课程简介: | **Robert S. Engelmore Memorial Award Lecture** - Cancer results from finite genomic mutations that biotechnology can easily list, and that we can mostly understand and reason about in terms of the underlying biochemistry. Tragically, the scientific and medical communities are searching for cures using an incredibly inefficient non-adaptive strategy, where the costs of experiments are measured in lives, as well as money, and where we capture only a small portion of the genomics and outcomes data, i.e., in clinical trials. Inspired by my career experiences as an AI researcher, Internet entrepreneur and cancer survivor, I am attempting to redress this situation through Cancer Commons, a "rapid learning" community of patients, physicians and researchers. Our goal is to cure cancer by collecting the genomic and response data from thousands of adaptively-planned individual treatment experiments, integrating the resulting sparse fragments of evidence to infer the true causal mechanisms of tumors and drugs, and generalizing the resulting knowledge so that it can be applied to new cases. Each patient is treated in accord with the best available knowledge, and that knowledge is continually updated to benefit the next patient. Hopefully, this adaptive approach will efficiently climb the hill to find cures for cancer, one patient at a time |
关 键 词: | 癌症; 人工智能; 计算疾病 |
课程来源: | 视频讲座网 |
最后编审: | 2021-03-01:yumf |
阅读次数: | 47 |