# Weakly-Supervised Multilingual Medical NER for Symptom Extraction for Low-Resource Languages
## 3 Results
### Case Studies
An (B-TEST) MRI (I-TEST) of (I-TEST) the (I-TEST) was ordered to rule out a (B-PROBLEM) neurological (I-PROBLEM) cause (E-PROBLEM). A (B-TREAMENT) beta (I-TREAMENT)-(I-TREAMENT) blocker (E-TREAMENT) was prescribed to stabilize her (B-TEST) blood (I-TEST) pressure (E-TEST). The fine-tuned model demonstrates superior handling of \"colloquial\" symptom descriptions. When processing clinical terminology like \"neurological cause\" and \"beta-blocker\", both models maintained precise entity boundaries and correct classification. For non-clinical expressions, such as, \"body aches\" instead of \"myalgia\", the model identifies these as PROBLEM entities successfully, showing adaptability to patient-level language. In contrast, the existing model has issues with compound terms and informal expressions, particularly in maintaining consistent entity boundaries. Spanish sentences  
Fine-tuned model predictions:  
1. El paciente se quejo de fuertes (B-PROBLEM) dolores (E-PROBLEM) de cabeza y nauseas (S-PROBLEM) que habian persistido durante dos dias. Para aliviar los sintomas, se le receto paracetamol (S-TREAMENT) y se le aconsejo descansar y beber muchos liquidos. 2. El paciente presento sintomas (S-PROBLEM) de feibre (S-PROBLEM), tos y dolores (E-PROBLEM) corporals (E-PROBLEM). Se le realizo una (B-TEST) radiografia (E-TEST) de torax para descartar t una (B-PROBLEM) neumonia (E-PROBLEM). Se le receto un (B-TREAMENT) antibiotic (E-TREAMENT) y se le aconsejo descansar. 3. La paciente se quejo de mareos (S-PROBLEM), alteraciones (E-PROBLEM) de la vision (B-PROBLEM) y entumecimiento (B-PROBLEM) en (I-PROBLEM) las manos (E-PROBLEM). Se ordeno una (B-TEST) resonancia (I-TEST) magnetica (E-TEST) del (I-TEST) cerebro (E-TEST) para descartar t una causa (E-PROBLEM) neurologica (I-PROBLEM). Se le receto un (B-TREAMENT) betaloleucine (E-TREAMENT) para estabilizar su (B-TEST) presion (E-TEST) arterial (I-TEST). Existing model predictions:  
1. El paciente se quejo de fuertes dolores (B-DISO) de (I-DISO) cabeza (I-PROBLEM) y nauseas (B-DISO) que habian persistido durante dos dias. Para aliviar los sintomas (B-PROBLEM), se le receto paracetamol (B-CHEM) y se le aconsejo descansar (B-PROC) y beber muchos liquidos. 2. El paciente presento sintomas (B-DISO) de (I-DISO) feibre (I-DISO), tos (I-DISO) y dolores (B-DISO) corporals (I-DISO). Se le realizo una radiografia (B-PROC) de (I-PROC) torax (I-PROC) para descartar t una neumonia (B-DISO). Se le receto (B-PROC) un antibiotics (B-CHEM) y se le aconsejo descansar (B-PROC). 3. La paciente se quejo de mareos (B-DISO), alteraciones (B-DISO) de (I-DISO) la (I-DISO) vision (I-DISO) y entumecimiento (B-DISO) en (I-DISO) las (I-DISO) manos (I-DISO). Se ordeno una resonancia (B-PROC) magnetica (I-PROC) del (I-PROC) cerebro (I-PROC) para descartar t una causa neurologica. Se le receto un betalolqueante (B-CHEM) para estabilizar (B-PROC) su presion (B-PROC) arterial (I-PROC). 1. The patient complained of severe headaches and nausea that had persisted for two days. To relieve the symptoms, paracetamol was prescribed, and the patient was advised to rest and drink plenty of fluids. 2. The patient presented symptoms of fever, cough, and body aches. A chest X-ray was performed to rule out pneumonia. An antibiotic was prescribed, and the patient was advised to rest. 3. The patient complained of dizziness, vision disturbances, and numbness in the hands. An MRI of the brain was ordered to rule out a neurological cause. A beta-blocker was prescribed to stabilize her blood pressure. The distinction between clinical and colloquial language is especially evident in the Spanish examples. The model proposed in this paper processed both formal medical terms (\"resonancia magnetica\"--MRI) and everyday expressions (\"dolores de cabeza\"--headaches) effectively as coherent entities. The existing model showed a bias toward clinical terminology, using a rigid DISO/PROC/CHEM classification that accommodates natural patient expressions poorly.