Machine learning method for diagnosing thyroid cancer by adopting open ion source

The invention provides a machine learning method for diagnosing thyroid cancer by adopting an open ion source. The invention specifically provides a malignant tumor diagnosis system based on an open type open ion source, a sample pretreatment method for malignant tumor diagnosis based on the open type open ion source, a composition for building a machine learning model, and a non-diagnostic malignant tumor analysis method based on an open ion source. Compared with a previously provided method, more molecular information (mainly small molecular metabolites and phospholipid compounds) derived from malignant tumors can be obtained by adopting more effective samples (directly adopting thyroid puncture fluid), and a classifier is trained by adopting an internal standard and newly found classification features (the ratio of feature compounds), so that the more effective classification method can be provided for samples, and the diagnosis efficiency is greatly improved. 本发明提供了一种采用开放式离子源诊断甲状腺癌的机器学习方法。具体的，提供了一种基于开放式敞开