Create app.py

app.py

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+import streamlit as st
+import medspacy
+from medspacy.ner import TargetRule
+
+# Load the MedSpaCy model
+nlp = medspacy.load()
+
+target_symptoms=[
+    TargetRule('Abdominal pain', 'SYMPTOM'),
+    TargetRule('Abdominal swelling', 'SYMPTOM'),
+    TargetRule('Loss of appetite', 'SYMPTOM'),
+    TargetRule('Weight loss', 'SYMPTOM'),
+    TargetRule('Nausea', 'SYMPTOM'),
+    TargetRule('Vomiting', 'SYMPTOM'),
+    TargetRule('Fatigue', 'SYMPTOM'),
+    TargetRule('Jaundice', 'SYMPTOM'),
+    TargetRule('Dark urine', 'SYMPTOM'),
+    TargetRule('Easy bleeding', 'SYMPTOM'),
+    TargetRule('Easy bruising', 'SYMPTOM'),
+    TargetRule('Right upper abdominal mass', 'SYMPTOM'),
+    TargetRule('Pale stools', 'SYMPTOM'),
+    TargetRule('Itchy skin', 'SYMPTOM'),
+    TargetRule('Chronic indigestion', 'SYMPTOM'),
+    TargetRule('Feeling of fullness in upper abdomen', 'SYMPTOM'),
+    TargetRule('New-onset diabetes', 'SYMPTOM'),
+    TargetRule('Confusion', 'SYMPTOM'),
+    TargetRule('Hinching', 'SYMPTOM'),
+    TargetRule('Bilirubin', 'SYMPTOM')
+]
+
+target_condition=[
+    TargetRule('Hepatic Cancer','CONDITION'),
+    TargetRule('Hepatocellular Carcinoma','CONDITION'),
+    TargetRule('HCC','CONDITION'),
+    TargetRule('Cholangiocarcinoma','CONDITION'),
+    TargetRule('Metastatic Liver Cancer','CONDITION'),
+    TargetRule('Liver Metastases','CONDITION'),
+    TargetRule('Cirrhosis','CONDITION'),
+    TargetRule('Hepatitis','CONDITION'),
+    TargetRule('Fibrolamellar Hepatocellular Carcinoma','CONDITION'),
+    TargetRule('Liver Resection','CONDITION'),
+    TargetRule('Liver cancer','CONDITION'),
+    TargetRule('Primary liver cancer','CONDITION'),
+    TargetRule('Hepatoma','CONDITION'),
+    TargetRule('Hepatic carcinoma','CONDITION')
+]
+
+target_diagnosis=[
+    TargetRule('Computed Tomography scan','DIAGNOSIS'),
+    TargetRule('CT scan','DIAGNOSIS'),
+    TargetRule('Magnetic Resonance Imaging','DIAGNOSIS'),
+    TargetRule('MRI','DIAGNOSIS'),
+    TargetRule('Positron Emission Tomography','DIAGNOSIS'),
+    TargetRule('PET scan','DIAGNOSIS'),
+    TargetRule('Ultrasound','DIAGNOSIS'),
+    TargetRule('Sonography','DIAGNOSIS'),
+    TargetRule('Biopsy','DIAGNOSIS'),
+    TargetRule('Blood tests','DIAGNOSIS'),
+    TargetRule('Laboratory tests','DIAGNOSIS'),
+    TargetRule('Endoscopy','DIAGNOSIS'),
+    TargetRule('Colonoscopy','DIAGNOSIS'),
+    TargetRule('Sigmoidoscopy','DIAGNOSIS'),
+    TargetRule('Liver Function Tests','DIAGNOSIS'),
+    TargetRule('LFTs','DIAGNOSIS'),
+    TargetRule('Tumor Marker Tests','DIAGNOSIS'),
+    TargetRule('Alpha-fetoprotein test','DIAGNOSIS'),
+    TargetRule('AFP test','DIAGNOSIS'),
+    TargetRule('Des-gamma-carboxy prothrombin test','DIAGNOSIS'),
+    TargetRule('DCP test','DIAGNOSIS'),
+    TargetRule('Liver biopsy blood test markers','DIAGNOSIS'),
+    TargetRule('Computerized Axial Tomography scan','DIAGNOSIS'),
+    TargetRule('CAT scan','DIAGNOSIS'),
+    TargetRule('Magnetic Resonance Imaging','DIAGNOSIS'),
+    TargetRule('MRI','DIAGNOSIS'),
+    TargetRule('Electrocardiogram','DIAGNOSIS'),
+    TargetRule('ECG','DIAGNOSIS'),
+    TargetRule('EKG','DIAGNOSIS'),
+    TargetRule('Electroencephalogram','DIAGNOSIS'),
+    TargetRule('EEG','DIAGNOSIS'),
+    TargetRule('Complete Blood Count','DIAGNOSIS'),
+    TargetRule('CBC','DIAGNOSIS'),
+    TargetRule('Blood Urea Nitrogen','DIAGNOSIS'),
+    TargetRule('BUN','DIAGNOSIS'),
+    TargetRule('Creatinine Clearance Test','DIAGNOSIS'),
+    TargetRule('CCT','DIAGNOSIS'),
+    TargetRule('Human Chorionic Gonadotropin','DIAGNOSIS'),
+    TargetRule('','DIAGNOSIS'),
+    TargetRule('HCG','DIAGNOSIS'),
+    TargetRule('Prostate-Specific Antigen','DIAGNOSIS'),
+    TargetRule('PSA','DIAGNOSIS'),
+    TargetRule('Thyroid Stimulating Hormone','DIAGNOSIS'),
+    TargetRule('TSH','DIAGNOSIS'),
+    TargetRule('Serum Glucose Test','DIAGNOSIS'),
+    TargetRule('SGT','DIAGNOSIS'),
+    TargetRule('Hemoglobin A1c','DIAGNOSIS'),
+    TargetRule('HbA1c','DIAGNOSIS'),
+    TargetRule('International Normalized Ratio','DIAGNOSIS'),
+    TargetRule('INR','DIAGNOSIS'),
+    TargetRule('Alanine Aminotransferase','DIAGNOSIS'),
+    TargetRule('ALT','DIAGNOSIS'),
+    TargetRule('Aspartate Aminotransferase','DIAGNOSIS'),
+    TargetRule('AST','DIAGNOSIS'),
+    TargetRule('C-reactive Protein','DIAGNOSIS'),
+    TargetRule('CRP','DIAGNOSIS')
+    
+]
+
+target_drugs=[
+    TargetRule('Sorafenib','DRUGS'),
+    TargetRule('Lenvatinib','DRUGS'),
+    TargetRule('Regorafenib','DRUGS'),
+    TargetRule('Cabozantinib','DRUGS'),
+    TargetRule('Sunitinib','DRUGS'),
+    TargetRule('Ramucirumab','DRUGS'),
+    TargetRule('Pembrolizumab','DRUGS'),
+    TargetRule('Atezolizumab','DRUGS'),
+    TargetRule('Bevacizumab','DRUGS'),
+    TargetRule('Nivolumab','DRUGS'),
+    TargetRule('Ipilimumab','DRUGS'),
+    TargetRule('Tremelimumab','DRUGS'),
+    TargetRule('Cisplatin','DRUGS'),
+    TargetRule('Oxaliplatin','DRUGS'),
+    TargetRule('Gemcitabine','DRUGS'),
+    TargetRule('5-Fluorouracil','DRUGS'),
+    TargetRule('Cetuximab','DRUGS'),
+    TargetRule('Panitumumab','DRUGS'),
+    TargetRule('Erlotinib','DRUGS'),
+    TargetRule('Trametinib','DRUGS'),
+    TargetRule('Aflibercept','DRUGS'),
+    TargetRule('Doxorubicin','DRUGS'),
+    TargetRule('Mitomycin C','DRUGS'),
+    TargetRule('Tegafur','DRUGS'),
+    TargetRule('Carboplatin','DRUGS'),
+    TargetRule('Docetaxel','DRUGS'),
+    TargetRule('Mitoxantrone','DRUGS'),
+    TargetRule('Topotecan','DRUGS'),
+    TargetRule('Irinotecan','DRUGS'),
+    TargetRule('Everolimus','DRUGS'),
+    TargetRule('Tas-102','DRUGS'),
+    TargetRule('Pazopanib','DRUGS'),
+    TargetRule('Liposomal irinotecan','DRUGS'),
+    TargetRule('Trifluridine','DRUGS'),
+    TargetRule('Raltitrexed','DRUGS'),
+    TargetRule('Olaparib','DRUGS'),
+    TargetRule('Durvalumab','DRUGS'),
+    TargetRule('Avelumab','DRUGS')
+    
+]
+
+
+# Add custom target rules to the medspacy_target_matcher component
+nlp.get_pipe('medspacy_target_matcher').add(target_symptoms)
+nlp.get_pipe('medspacy_target_matcher').add(target_condition)
+nlp.get_pipe('medspacy_target_matcher').add(target_diagnosis)
+nlp.get_pipe('medspacy_target_matcher').add(target_drugs)
+
+def extract_entities(text):
+    doc = nlp(text)
+    entities = {}
+    for ent in doc.ents:
+        label = ent.label_
+        if label not in entities:
+            entities[label] = []
+        entities[label].append(ent.text)
+    return entities
+
+# Streamlit UI
+st.title("Medical Entity Extraction")
+text_input = st.text_area("Enter medical text here:")
+if st.button("Extract Entities"):
+    entities = extract_entities(text_input)
+    st.write("Extracted Entities:")
+    for label, texts in entities.items():
+        st.write(f"{label}: {', '.join(texts)}")