Orris

Write a proper full medical record of this patient Nguyen duc long with the pdf I uploaded using the medical record template format. I want to score 10/10. So, please help me to write the proper medical record in this format for this patient.

I'll start by reading both PDFs to understand the patient information and the template format.
Reading File
Now let me extract text from both PDFs simultaneously.
Running Command

cd /home/daytona/workspace && python3 -c " import pdfplumber # Extract patient PDF print('=== PATIENT PDF ===') with pdfplumber.open('/home/daytona/workspace/attachments/e150d99d-06c5-41de-b285-1f2fc654cb98/Adobe Scan Jul 14, 2026_1.pdf') as pdf: for i, page in enumerate(pdf.pages): print(f'--- Page {i+1} ---') text = page.extract_text() print(text) print() "

The PDFs are scanned images. Let me use OCR and also analyse the images visually.
Running Command

python3 -c " from pypdf import PdfReader reader = PdfReader('/home/daytona/workspace/attachments/e150d99d-06c5-41de-b285-1f2fc654cb98/Adobe Scan Jul 14, 2026_1.pdf') print('Patient PDF pages:', len(reader.pages)) reader2 = PdfReader('/home/daytona/workspace/attachments/e150d99d-06c5-41de-b285-1f2fc654cb98/medical record template.pdf') print('Template PDF pages:', len(reader2.pages)) "

These are scanned PDFs - I need to convert them to images and use OCR. Let me extract images from both PDFs and analyse them.
Running Command

python3 -c " import subprocess # Convert PDFs to images using pdftoppm import os os.makedirs('/home/daytona/workspace/pdf_images/patient', exist_ok=True) os.makedirs('/home/daytona/workspace/pdf_images/template', exist_ok=True) result1 = subprocess.run(['pdftoppm', '-r', '150', '-png', '/home/daytona/workspace/attachments/e150d99d-06c5-41de-b285-1f2fc654cb98/Adobe Scan Jul 14, 2026_1.pdf', '/home/daytona/workspace/pdf_images/patient/page'], capture_output=True, text=True) print('Patient conversion:', result1.returncode, result1.stderr) result2 = subprocess.run(['pdftoppm', '-r', '150', '-png', '/home/daytona/workspace/attachments/e150d99d-06c5-41de-b285-1f2fc654cb98/medical record template.pdf', '/home/daytona/workspace/pdf_images/template/page'], capture_output=True, text=True) print('Template conversion:', result2.returncode, result2.stderr) import os patient_files = sorted(os.listdir('/home/daytona/workspace/pdf_images/patient/')) template_files = sorted(os.listdir('/home/daytona/workspace/pdf_images/template/')) print('Patient pages:', patient_files) print('Template pages:', template_files) "

Running Command

python3 -c " import subprocess, os os.makedirs('/home/daytona/workspace/pdf_images/patient', exist_ok=True) os.makedirs('/home/daytona/workspace/pdf_images/template', exist_ok=True) # Lower resolution, just first few pages result1 = subprocess.run(['pdftoppm', '-r', '100', '-png', '-f', '1', '-l', '5', '/home/daytona/workspace/attachments/e150d99d-06c5-41de-b285-1f2fc654cb98/Adobe Scan Jul 14, 2026_1.pdf', '/home/daytona/workspace/pdf_images/patient/page'], capture_output=True, text=True, timeout=50) print('Patient p1-5:', result1.returncode, result1.stderr[:200]) print(sorted(os.listdir('/home/daytona/workspace/pdf_images/patient/'))) " 2>&1

Good - 18 patient pages already extracted. Now let me get the template pages and then use OCR on all of them.
Running Command

python3 -c " import subprocess, os result2 = subprocess.run(['pdftoppm', '-r', '100', '-png', '/home/daytona/workspace/attachments/e150d99d-06c5-41de-b285-1f2fc654cb98/medical record template.pdf', '/home/daytona/workspace/pdf_images/template/page'], capture_output=True, text=True, timeout=50) print('Template:', result2.returncode, result2.stderr[:200]) print(sorted(os.listdir('/home/daytona/workspace/pdf_images/template/'))) " 2>&1

Now let me run OCR on all pages and also use analyse_media on the most important ones. Let me do OCR first on all pages.
Running Command

python3 -c " import subprocess, os # OCR all patient pages patient_dir = '/home/daytona/workspace/pdf_images/patient/' files = sorted(os.listdir(patient_dir)) all_text = [] for f in files: path = patient_dir + f result = subprocess.run(['tesseract', path, 'stdout', '-l', 'eng', '--psm', '1'], capture_output=True, text=True, timeout=30) all_text.append(f'=== {f} ===\n{result.stdout}') with open('/home/daytona/workspace/patient_ocr.txt', 'w') as out: out.write('\n'.join(all_text)) print('Done. Lines:', sum(len(t.split(chr(10))) for t in all_text)) " 2>&1

OCR is too slow. Let me use analyse_media on the most critical pages - the template pages and first few patient pages - to get the information visually.
Running Command

python3 -c " import subprocess, os # Just do first 3 patient pages with OCR, faster patient_dir = '/home/daytona/workspace/pdf_images/patient/' for i in range(1, 4): f = f'page-0{i}.png' result = subprocess.run(['tesseract', patient_dir+f, 'stdout', '--psm', '6'], capture_output=True, text=True, timeout=25) print(f'=== {f} ===') print(result.stdout[:2000]) " 2>&1

Good - I can see key patient info. Now let me OCR more pages and also analyse the template visually.
Running Command

python3 -c " import subprocess, os patient_dir = '/home/daytona/workspace/pdf_images/patient/' # Pages 4-10 for i in [4,5,6,7,8,9,10]: f = f'page-{i:02d}.png' if os.path.exists(patient_dir+f): result = subprocess.run(['tesseract', patient_dir+f, 'stdout', '--psm', '6'], capture_output=True, text=True, timeout=20) print(f'=== {f} ===') print(result.stdout[:2500]) " 2>&1

Excellent data. Now let me OCR more pages (11-18) and also get the template pages.
Running Command

python3 -c " import subprocess, os patient_dir = '/home/daytona/workspace/pdf_images/patient/' for i in range(11, 19): f = f'page-{i:02d}.png' if os.path.exists(patient_dir+f): result = subprocess.run(['tesseract', patient_dir+f, 'stdout', '--psm', '6'], capture_output=True, text=True, timeout=20) print(f'=== {f} ===') print(result.stdout[:2500]) " 2>&1

Now let me OCR the template pages.
Running Command

python3 -c " import subprocess, os template_dir = '/home/daytona/workspace/pdf_images/template/' files = sorted(os.listdir(template_dir)) for f in files: result = subprocess.run(['tesseract', template_dir+f, 'stdout', '--psm', '6'], capture_output=True, text=True, timeout=20) print(f'=== {f} ===') print(result.stdout[:3000]) print() " 2>&1

Now I have all the information I need. The template is an ORTHOPAEDIC CASE RECORD TEMPLATE - postoperative format since surgery was done. Let me also analyse the template page 4 visually (it appeared blank but might have content), and now write the full medical record.
analyse_media
I have enough data to write the complete medical record. Let me now compile everything and write it as a Word document (or PDF).
This is a shared conversation. Sign in to Orris to start your own chat.