private DrugSuggestionInputModel PrepareDrugSuggestionInput(MedicalEntityResponse entityResponse, PatientDto patientDto)
{
var modelResult = new DrugSuggestionInputModel();
foreach (var item in entityResponse.MedicalConditions)
{
if (item.Text.Equals("fever", StringComparison.OrdinalIgnoreCase))
{
modelResult.Fever = true;
}
if (item.Text.Equals("vomiting", StringComparison.OrdinalIgnoreCase) || item.Text.Equals("vomite", StringComparison.OrdinalIgnoreCase))
{
modelResult.Vomiting = true;
}
if (item.Text.Equals("headache", StringComparison.OrdinalIgnoreCase) ||
item.Text.Equals("head ache", StringComparison.OrdinalIgnoreCase))
{
modelResult.Headache = true;
}
if (item.Text.Equals("diarrhea", StringComparison.OrdinalIgnoreCase))
{
modelResult.Diarrhea = true;
}
}
modelResult.Age = patientDto?.Age;
modelResult.Weight = patientDto?.Weight;
return(modelResult);
}
public async Task <List <string> > GetMedicineSuggestionByPatientSymptoms(string externalPatientId)
{
var modelResult = new DrugSuggestionInputModel();
try
{
//get patient demographic information
var patientInfo = await _patientService.Get(externalPatientId);
var patientProblems = await _problemService.GetAll(externalPatientId, 1);
if (patientProblems.Count > 0)
{
foreach (var problem in patientProblems.Results)
{
if (problem.Name.Equals("fever", StringComparison.OrdinalIgnoreCase))
{
modelResult.Fever = true;
}
if (problem.Name.Equals("vomiting", StringComparison.OrdinalIgnoreCase) || problem.Name.Equals("vomite", StringComparison.OrdinalIgnoreCase))
{
modelResult.Vomiting = true;
}
if (problem.Name.Equals("headache", StringComparison.OrdinalIgnoreCase) ||
problem.Name.Equals("head ache", StringComparison.OrdinalIgnoreCase))
{
modelResult.Headache = true;
}
if (problem.Name.Equals("diarrhea", StringComparison.OrdinalIgnoreCase))
{
modelResult.Diarrhea = true;
}
}
}
modelResult.Age = patientInfo?.Age;
modelResult.Weight = patientInfo?.Weight;
if (_rootConfiguration.AWSAIServiceEnabled)
{
var response = await InvokeAIServiceAsync(modelResult);
if (response.IsSuccess != true)
{
return(null);
}
//convert to medicine list
var(medicineList1, rawList1) = GetMedicineList(response.RawResult);
return(rawList1);
}
else
{
var tempdata = await LoadSampleResponseFromFile();
var(medicineList, rawList) = GetMedicineList(tempdata);
return(rawList);
}
}
catch (Exception ex)
{
throw;
}
}
public async Task <MLServiceResponse> InvokeAIServiceAsync(DrugSuggestionInputModel inputModel)
{
MLServiceResponse mlResponse = new MLServiceResponse();
using (var client = new HttpClient())
{
var scoreRequest = new
{
Inputs = new Dictionary <string, List <Dictionary <string, string> > >()
{
{
"input1",
new List <Dictionary <string, string> >()
{
new Dictionary <string, string>()
{
{
"Age", inputModel.Age?.ToString()
},
{
"Weight", inputModel.Weight?.ToString()
},
{
"Pain", inputModel.Pain == true ? "1":"0"
},
{
"Fever", inputModel.Fever == true ? "1":"0"
},
{
"Vomiting", inputModel.Vomiting == true ? "1":"0"
},
{
"Diarrhea", inputModel.Diarrhea == true ? "1":"0"
},
{
"Headache", inputModel.Headache == true ? "1":"0"
},
}
}
},
},
GlobalParameters = new Dictionary <string, string>()
{
}
};
const string apiKey = "IRKObndmpuYuwSHXmtS0YZZhygs/cWuF7v5cgvebWzf2dTtBx4ezcm7D3xtps8j5zFjlmfQ8ovcX+yTMLYz08g=="; // Replace this with the API key for the web service
client.DefaultRequestHeaders.Authorization = new AuthenticationHeaderValue("Bearer", apiKey);
client.BaseAddress = new Uri("https://ussouthcentral.services.azureml.net/workspaces/96f334343d5348109dd6b13b5f3c6743/services/ff04126f8bd04e21a4c81c0cc2e2141e/execute?api-version=2.0&format=swagger");
// WARNING: The 'await' statement below can result in a deadlock
// if you are calling this code from the UI thread of an ASP.Net application.
// One way to address this would be to call ConfigureAwait(false)
// so that the execution does not attempt to resume on the original context.
// For instance, replace code such as:
// result = await DoSomeTask()
// with the following:
// result = await DoSomeTask().ConfigureAwait(false)
HttpResponseMessage response = await client.PostAsJsonAsync("", scoreRequest);
if (response.IsSuccessStatusCode)
{
string result = await response.Content.ReadAsStringAsync();
// mlResponse = JsonConvert.DeserializeObject<MLServiceResponse>(result);
mlResponse.RawResult = result;
mlResponse.IsSuccess = true;
return(mlResponse);
}
else
{
Console.WriteLine(string.Format("The request failed with status code: {0}", response.StatusCode));
// Print the headers - they include the requert ID and the timestamp,
// which are useful for debugging the failure
Console.WriteLine(response.Headers.ToString());
string responseContent = await response.Content.ReadAsStringAsync();
mlResponse.Error("Error occurred while calling ML Service on Cloud", responseContent);
return(mlResponse);
}
}
}
