公开(公告)号：US20150006445A1

公开(公告)日：2015-01-01

申请号：US14320214

申请日：2014-06-30

申请人： Stephen Charles Benz ,  Shahrooz Rabizadeh ,  Christopher Szeto ,  Paul Weingarten ,  Chunlin Tao

发明人： Stephen Charles Benz ,  Shahrooz Rabizadeh ,  Christopher Szeto ,  Paul Weingarten ,  Chunlin Tao

IPC分类号： G06F19/00 ,  G06N5/04 ,  G06N99/00

CPC分类号： G16H50/20

摘要： The present inventive subject matter provides apparatus, systems, and methods in which a diagnostic test is identified, where the diagnostic test is for determining whether a particular treatment is effective for a particular patient based on one or more characteristics of a patient's cells. When a treatment is developed with the potential to treat one or more diseases, the drug can have different effects on different cell lines related to the diseases. A machine learning system is programmed to infer a measurable cell characteristic, out of many different measurable cell characteristics, that has a desirable correlation with the sensitivity data of different cell lines to a treatment. The machine learning system is programmed to then determine, based on the correlation, a threshold level of the cell characteristic the patient should exhibit in order to recommend administering the treatment.

摘要翻译： 本发明的主题提供了其中识别诊断测试的装置，系统和方法，其中诊断测试用于基于患者细胞的一个或多个特征来确定特定治疗是否对特定患者有效。 当开发具有治疗一种或多种疾病潜力的治疗时，该药物可以对与疾病相关的不同细胞系具有不同的作用。 机器学习系统被编程为推断出许多不同可测量的细胞特征中的可测量细胞特征，其与不同细胞系对治疗的敏感性数据具有期望的相关性。 机器学习系统被编程为然后基于相关性来确定患者应该展示的细胞特征的阈值水平以推荐施用治疗。