Classification of cancer condition, in a plurality of different cancer conditions, for a species, is provided in which, for each training subject in a plurality of training subjects, there is obtained a cancer condition and a genotypic data construct including genotypic information for the respective training subject. Genotypic constructs are formatted into corresponding vector sets comprising one or more vectors. Vector sets are provided to a network architecture including a convolutional neural network path comprising at least a first convolutional layer associated with a first filter that comprise a first set of filter weights and a scorer. Scores, corresponding to the input of vector sets into the network architecture, are obtained from the scorer. Comparison of respective scores to the corresponding cancer condition of the corresponding training subjects is used to adjust the filter weights thereby training the network architecture to classify cancer condition.提供在多種不同癌症病況中對一物種之一癌症病況進行分類，其中對於多個訓練個體中之每一訓練個體，獲得所述各別訓練個體之癌症病況及包含其基因型資訊之基因型資料構築體。將基因型構築體格式化成包括一個或多個向量之相應向量集。將向量集提供至一包含一卷積神經網路路徑之網路架構，所述卷積神經網路路徑包括至少一個與一第一濾波器相關聯之第一卷積層，所述第一濾波器包括一第一組濾波器權重；及一評分器。對應於向量集於所述網路架構中之輸入的分數係自所述評分器獲得。使用各別分數與所述相應訓練個體之相應癌症病況的比較來調整所述濾波器權重，由此訓練所述網路架構以對癌症病況進行分類。
