Figure 1
Clinical knowledge and data science modeling work in tandem to drive hypothesis generation. In our approach, we combine machine learning methods with clinical knowledge to generate hypothesized patient sub-groups and factors that affect patient outcomes. The collaboration between clinical insight and machine learning modeling informs the generation of new hypotheses which may then be tested in further research. The yellow arrow indicates the critical interplay between clinical knowledge and machine learning modeling: clinical knowledge informs the construction of models and the results of models are checked against clinical knowledge.
