Version for submission to PLOS CB

Data_Curation_VetOnly.ipynb

@@ -0,0 +1,68 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4fafef82-3964-415b-9979-7c96f76c73ad",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "53aa7adc-fc8f-4a34-9b00-80b78c5cda6b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Load dataset\n",
+    "data = pd.read_csv('/Data/TB_Diagnostics/inputVars.csv', low_memory=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "81e05216-f5d8-4c13-8997-53d5f7997ee0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Remove rows with no vet practice information\n",
+    "data_vet_only = data.dropna(subset=['vetPractice'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1a2387f4-2943-4864-a5a5-ca4e6e87f9e4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Output\n",
+    "data_vet_only.to_csv('/Data/TB_Diagnostics/inputVars_VetOnly.csv', index=False)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

README

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+# bTB-diagnostics
+
+This project trains a Histogram Boosted Regression Tree model on data from Bovine Tuberculosis (bTB) testing and cattle herd metadata to predict the risk of bTB outbreak.
+
+This can be used to improve the herd-level sensitivity or specificity of the diagnostic test and also to analyse the risk factors involved in predicting bTB outbreaks.
+
+The project consists of a number of Jupyter Notebooks:
+(i) Data_Curation* -- processes the various inpiut data into a matrix for model training.
+(ii) bTB-Diagnostic_2020_v4_crossVal+tuning* -- code that trains the various models.
+(iii) bTB-Diagnostic_2020_final_model* -- code that performs various analysis on the models.
+(iv) Vet_Data_Analysis -- code that performs some extra analysis on the veterinary data.
+
+Further details can be found in the preprint (paper in sumbission for peer review) at: https://arxiv.org/abs/2404.03678