System and method for molecular diagnosis of depression based on boosting classification
作者： Amit Chakraborty , Dorin Comaniciu , Lu-yong Wang
DOI:
关键词: Artificial intelligence 、 Data mining 、 Mass spectrometric 、 Boosting (machine learning) 、 Alternating decision tree 、 Mathematics 、 Pattern recognition
摘要: A method for diagnosing depression includes providing surface-enhanced laser desorption/ionisation mass spectrometric (SELDI-MS) data of a plurality proteins, said obtained from patient and comprising peak values, analysing values with an alternating decision tree set tests peaks associated prediction wherein is predictive if sum the greater than 1.0.
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