Analysis and identification of malignant cells with artificial intelligence technique (SDVHA

Early cancer detection has significant clinical value, but there remains no single method that can comprehensively identify multiple types of early-stage cancer. Here, we SDVH Analytics (SDVHA) is an application to build a local database of treatment planning data for historical comparisons and statistical analysis. SDVHA builds a SQ database of SDVHs and various planning parameters from DICOM files (i.e., Plan, Structure, Dose). In addition to viewing SDVH data, this software provides methods to download queried data, cre- ate time-series plots, calculate correlations, generate multi-variable linear & machine learning regressions, and generate control charts.

Keywords:

SDVHA , Python , DICOM RT , treatment