Systems and methods for determining origin cells from variant recognition data

• Main Authors: LIN HENRY, KURZ DANIEL, TABARY EMRE, LOVEJOY ADRIAN, LONG KEVIN
• Format: Patent
• Language: Chinese; English
• Published: 18.03.2022
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; HANDLING RECORD CARRIERS; INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS; PHYSICS; PRESENTATION OF DATA; RECOGNITION OF DATA; RECORD CARRIERS

The present invention relates generally to classification of biological samples, and more particularly to classification of origin cells. In particular, some embodiments of the present invention relate to diffuse large B-cell lymphoma origin cell classification using a machine learning model. The machine learning model may be based on a decision tree such as a random forest algorithm or a gradient boosted decision tree. Characteristics of the model may be determined by analyzing variant data of plasma or blood samples from a plurality of subjects suffering from a disease. 本发明总体涉及生物学样品的分类，并且更具体地涉及起源细胞分类。特别地，本发明的一些实施方案涉及使用机器学习模型进行的弥漫性大B细胞淋巴瘤起源细胞分类。所述机器学习模型可以基于诸如随机森林算法或梯度提升决策树之类的决策树。可以通过分析来自多个患有疾病的受试者的血浆或血液样品的变体数据来确定所述模型的特征。