Kya tum is ipd file ko dekh kr diagnosis bana sakte ho
python3 -c " import pdfplumber pdf_path = '/home/daytona/workspace/attachments/ef38ac52-78ea-476f-8448-5745e2b031c1/ICU2 Abu Osama(pdfgear.com) (1).pdf' with pdfplumber.open(pdf_path) as pdf: print(f'Total pages: {len(pdf.pages)}') for i, page in enumerate(pdf.pages): print(f'\\n=== PAGE {i+1} ===') text = page.extract_text() if text: print(text) else: print('[No text extracted]') "
python3 -c " from pypdf import PdfReader import base64 pdf_path = '/home/daytona/workspace/attachments/ef38ac52-78ea-476f-8448-5745e2b031c1/ICU2 Abu Osama(pdfgear.com) (1).pdf' reader = PdfReader(pdf_path) print(f'Pages: {len(reader.pages)}') # Check if there are images in the pages for i in range(min(3, len(reader.pages))): page = reader.pages[i] print(f'Page {i+1} resources: {list(page.get(\"/Resources\", {}).keys()) if page.get(\"/Resources\") else \"none\"}') if '/XObject' in str(page.get('/Resources', {})): print(f' Has XObjects (likely images)') "
python3 -c " import fitz # PyMuPDF import os pdf_path = '/home/daytona/workspace/attachments/ef38ac52-78ea-476f-8448-5745e2b031c1/ICU2 Abu Osama(pdfgear.com) (1).pdf' output_dir = '/home/daytona/workspace/ipd_pages/' os.makedirs(output_dir, exist_ok=True) doc = fitz.open(pdf_path) print(f'Total pages: {len(doc)}') # Convert first 10 pages to images for i in range(min(10, len(doc))): page = doc[i] mat = fitz.Matrix(2, 2) # 2x zoom for better quality pix = page.get_pixmap(matrix=mat) img_path = f'{output_dir}page_{i+1:02d}.png' pix.save(img_path) print(f'Saved page {i+1}: {img_path} ({pix.width}x{pix.height})') doc.close() print('Done!') "
mkdir -p /home/daytona/workspace/ipd_pages && pdftoppm -r 200 -png "/home/daytona/workspace/attachments/ef38ac52-78ea-476f-8448-5745e2b031c1/ICU2 Abu Osama(pdfgear.com) (1).pdf" /home/daytona/workspace/ipd_pages/page && ls /home/daytona/workspace/ipd_pages/ | head -15
mkdir -p /home/daytona/workspace/ipd_pages && pdftoppm -r 150 -png -f 1 -l 5 "/home/daytona/workspace/attachments/ef38ac52-78ea-476f-8448-5745e2b031c1/ICU2 Abu Osama(pdfgear.com) (1).pdf" /home/daytona/workspace/ipd_pages/page && ls /home/daytona/workspace/ipd_pages/
python3 -c " import base64 import json # Read page 1 as base64 to use with vision with open('/home/daytona/workspace/ipd_pages/page-01.png', 'rb') as f: data = base64.b64encode(f.read()).decode() print(f'Page 1 base64 length: {len(data)}') print('First 100 chars:', data[:100]) "
tesseract /home/daytona/workspace/ipd_pages/page-01.png /home/daytona/workspace/ipd_pages/page-01_ocr -l eng+urd 2>&1 && cat /home/daytona/workspace/ipd_pages/page-01_ocr.txt
# Try OCR on multiple key pages with English only for page in 01 02 03 04 05 06 07 08; do echo "=== PAGE $page ===" tesseract /home/daytona/workspace/ipd_pages/page-${page}.png stdout -l eng 2>/dev/null echo "" done
for page in 09 10 11 12 13 14 15 16 17 18 19 20; do echo "=== PAGE $page ===" tesseract /home/daytona/workspace/ipd_pages/page-${page}.png stdout -l eng 2>/dev/null echo "" done
pdftoppm -r 150 -png -f 21 -l 38 "/home/daytona/workspace/attachments/ef38ac52-78ea-476f-8448-5745e2b031c1/ICU2 Abu Osama(pdfgear.com) (1).pdf" /home/daytona/workspace/ipd_pages/page && ls /home/daytona/workspace/ipd_pages/ | grep -E "page-2[1-9]|page-3"
for page in 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38; do echo "=== PAGE $page ===" tesseract /home/daytona/workspace/ipd_pages/page-${page}.png stdout -l eng 2>/dev/null echo "" done
for page in 21 22 23 24 25; do echo "=== PAGE $page ===" timeout 10 tesseract /home/daytona/workspace/ipd_pages/page-${page}.png stdout -l eng 2>/dev/null || echo "[timeout]" echo "" done
for page in 26 27 28 29 30 31 32; do echo "=== PAGE $page ===" timeout 10 tesseract /home/daytona/workspace/ipd_pages/page-${page}.png stdout -l eng 2>/dev/null || echo "[timeout/error]" echo "" done
| Priority | Diagnosis | Supporting Evidence |
|---|---|---|
| 1st | Rheumatic Fever with Carditis + Sepsis | ASO+, tachycardia, short PR, hepatosplenomegaly, high CRP, leukocytosis |
| 2nd | Infective Endocarditis (SBE) | ASO+, fever, hepatosplenomegaly, AKI (embolic), anemia, high CRP |
| 3rd | Enteric Fever (Typhoid) with complications | Hepatosplenomegaly, hyponatremia, anemia, leukocytosis (resolving) |
| 4th | Visceral Leishmaniasis (Kala-Azar) | Massive splenomegaly (148mm), hepatomegaly, anemia, hypoalbuminemia - endemik area (Mau, UP) |
Visceral Leishmaniasis (Kala-Azar) with secondary bacterial sepsisYa Acute Rheumatic Fever with Carditis + Sepsis + AKI
⚕️ Note: Yeh analysis available lab reports, ECG, Echo, USG aur clinical data ke basis par hai. Final diagnosis ke liye treating physician ki clinical examination aur additional investigations zaroori hain. Yeh report medicolegal use ke liye nahi hai.