# Clinical Trial Classification of SNS24 Calls with Neural Networks
## 6 Analysis among Similar Clinical Symptoms  
In this section, we performed an analysis of the trained neural network models when dealing with classes that have similar clinical symptoms. According to the SNS24 call center, there is some degree of overlap between clinical pathways. Although this overlap is expected, it may make cause the clinical decision making process to be more complex. Figures 9 and 10 presents two example groups that includes clinical pathways with similar symptoms.  
Figure 9 presents an example group that includes six clinical pathways with similar symptoms. They are _Pr. da orfaringe_ (_Oropharynx problem_), _Pr. deasma ou pieira_ (_Asthma or wheezing problem_), _Pr. nasal_ (_Nasal problem_), _Pr. respiratorio_ (_Respiratory problem_), _Sindrome gripal_ (_Flu syndrome_), and _Tosse_ (_Cough_).  
Using the pre-trained neural network model, we built the heatmap for these clinical pathways. Taking _Oropharynx problem_ for example, 64% of the cases are rightly classified, 4% are wrongly classified as _Nasal problem_, 11% as _Flu syndrome_, 8% as _Cough_, and 13% as the other clinical pathways. On the other way around, 3% _Flu syndrome_ cases are wrongly classified as _Oropharynx problem_, and 12 % as _Cough_.  
These observations suggest that _Flu syndrome_ cases are more likely to be classified as _Cough_ than _Oropharynx problem_. But on the other way, the _Oropharynx problem_ case is more likely to be classified as _Flu syndrome_ than _Cough_. Furthermore, we find that 1% of the _Cough_ cases are wrongly classified as _Oropharynx problem_ and 8% as _Flu syndrome_, which means that _Cough_ cases are more likely to be classified as _Flu syndrome_.  
Joining these above observations, we can deduce that it is harder to distinguish between _Cough_ and _Flu syndrome_ cases, and in practical application, the nurses should pay more attention to identifying these two types of clinical pathways.  
Figure 9: Analysis among clinical pathways with similar clinical symptoms using the trained neural network model. This group includes six clinical pathways: _Pr. da orfaringe_ (_Oropharynx problem_), _Pr. deasma ou pieira_ (_Asthma or wheezing problem_), _Pr. nasal_ (_Nasal problem_), _Pr. respiratorio_ (_Respiratory problem_), _Sindrome gripal_ (_Flu syndrome_), _Tosse_ (_Cough_).  
Figure 10 presents an example group that includes three clinical pathways with similar symptoms. They are _Diarreia_ (_Diarrhea_), _Dor abdominal_ (_Abdominal pain_), and _Nausea e vomitos_ (_Nausea and vomiting_).  
As can be observed, an average of 80% cases in this group can be rightly classified with the built neural network model. This means that the built model can provide useful suggestions to the SNS24 nurses when distinguish the clinical pathways that fall into this group.  
We also find that for _Abdominal pain_, 6% are wrongly classified as _Nausea and vomiting_, and 3% as _Diarrhea_. This means that _Abdominal pain_ is more likely to be classified as _Nausea and vomiting_. Similarly, when observing _Nausea and vomiting_, 6% are classified as _Abdominal pain_ and 1% as _Diarrhea_. These findings suggest that _Abdominal pain_ and _Nausea and vomiting_ cases are harder to be distinguished in this group. These results provide valuable analysis for the SNS24 Health Calls center, for example, helping to do deep analysis between similar symptoms.