Read the file properly Make the diagnosis Patient is chronic alocholic ( eye opener), smoker This facial appearance is from 3 months Explain me everything what is abnormal from reports Corelate with the image of face Give me differentials and r/o each of them And finally management
facial edema AND differential diagnosis
facial swelling unilateral periorbital edema red flags orbital cellulitis superior vena cava syndrome clinical guidance
~/
~/attachments/fd575d3b-15ee-4140-8348-0df0dae971b4
mkdir -p "/tmp/workspace/case-review" && python -c "from pypdf import PdfReader; p='/tmp/workspace/attachments/fd575d3b-15ee-4140-8348-0df0dae971b4/dad all reports merging.pdf'; r=PdfReader(p); print('PAGES',len(r.pages)); out=[]; [out.append('\\n===== PAGE %d =====\\n%s'%(i+1,(page.extract_text() or ''))) for i,page in enumerate(r.pages)]; open('/tmp/workspace/case-review/reports_extracted.txt','w',encoding='utf-8').write('\\n'.join(out)); print('CHARS',sum(len(x) for x in out))" && python -c "import fitz; p='/tmp/workspace/attachments/fd575d3b-15ee-4140-8348-0df0dae971b4/dad all reports merging.pdf'; d=fitz.open(p); print('PDF_PAGES',len(d)); [d[i].get_pixmap(matrix=fitz.Matrix(1.5,1.5),alpha=False).save('/tmp/workspace/case-review/page_%02d.png'%(i+1)) for i in range(len(d))]"
python -c "from pypdf import PdfReader; from pathlib import Path; p='/tmp/workspace/attachments/fd575d3b-15ee-4140-8348-0df0dae971b4/dad all reports merging.pdf'; o=Path('/tmp/workspace/case-review/pages'); o.mkdir(exist_ok=True); r=PdfReader(p); print('pages',len(r.pages));\nfor n,page in enumerate(r.pages,1):\n imgs=list(page.images); print(n,len(imgs),[(im.name,len(im.data)) for im in imgs]);\n for j,im in enumerate(imgs,1): open(o/f'p{n:02d}_{j}_{im.name}', 'wb').write(im.data)"
python -c "exec(\"from pypdf import PdfReader\\nfrom pathlib import Path\\np='/tmp/workspace/attachments/fd575d3b-15ee-4140-8348-0df0dae971b4/dad all reports merging.pdf'\\no=Path('/tmp/workspace/case-review/pages'); o.mkdir(exist_ok=True)\\nr=PdfReader(p)\\nprint('pages',len(r.pages))\\nfor n,page in enumerate(r.pages,1):\\n imgs=list(page.images)\\n print(n,len(imgs),[(im.name,len(im.data)) for im in imgs])\\n for j,im in enumerate(imgs,1):\\n open(o/f'p{n:02d}_{j}_{im.name}', 'wb').write(im.data)\\n\")"
python -c "exec(\"from PIL import Image,ImageDraw\\nfrom pathlib import Path\\nsrc=Path('/tmp/workspace/case-review/pages'); out=Path('/tmp/workspace/case-review/contact');out.mkdir(exist_ok=True)\\nfiles=[src/f'p{i:02d}_2_X2.jpg' for i in range(1,28)]\\nfor grp in range(3):\\n ims=[]\\n for k,f in enumerate(files[grp*9:(grp+1)*9],grp*9+1):\\n im=Image.open(f).convert('RGB'); im.thumbnail((400,550)); card=Image.new('RGB',(420,590),'white'); card.paste(im,((420-im.width)//2,30)); ImageDraw.Draw(card).text((10,8),f'PAGE {k}',fill='black'); ims.append(card)\\n sheet=Image.new('RGB',(1260,1770),'white')\\n for j,im in enumerate(ims): sheet.paste(im,((j%3)*420,(j//3)*590))\\n sheet.save(out/f'contact_{grp+1}.jpg',quality=92)\\n\")"
python -c "import importlib.util; print('pytesseract',importlib.util.find_spec('pytesseract')); print('easyocr',importlib.util.find_spec('easyocr')); print('rapidocr_onnxruntime',importlib.util.find_spec('rapidocr_onnxruntime')); import shutil; print('tesseract',shutil.which('tesseract'))"
pip install --user rapidocr-onnxruntime
You are assisting with an urgent clinical case review. The user uploaded a scanned 27-page PDF at /tmp/workspace/attachments/fd575d3b-15ee-4140-8348-0df0dae971b4/dad all reports merging.pdf. Thoroughly read every page by extracting the page images already saved at /tmp/workspace/case-review/pages/p01_2_X2.jpg through p27_2_X2.jpg. Use available visual/file tools as needed. Return: (1) chronological report list, each test/date, exact abnormal values and reference ranges if visible, (2) normal/reassuring results relevant to differential, (3) all imaging impressions, (4) an evidence-based clinical synthesis explaining the most likely unifying diagnosis but explicitly state limitations of scans/results. Do not invent any values. This is a medical query: follow mandatory medical library routing and obtain recent review search if necessary. Focus specifically on the facial/periorbital swelling presentation and alcohol/smoking.
~/case-review/pages
/skills/readonly/pubmed
facial edema alcohol smoking
facial periorbital edema differential diagnosis alcohol smoking clinical review
python -c "from PIL import Image; import pytesseract, glob, os; fs=sorted(glob.glob('/tmp/workspace/case-review/pages/p*_2_X2.jpg')); out=[]; [out.append('\n\n===== '+os.path.basename(f)+' =====\n'+pytesseract.image_to_string(Image.open(f))) for f in fs]; open('/tmp/workspace/case-review/ocr.txt','w').write(''.join(out)); print(len(fs), 'pages OCRd')"
python -c "from PIL import Image; import os; print([(f'p{i:02d}',Image.open(f'/tmp/workspace/case-review/pages/p{i:02d}_2_X2.jpg').size) for i in range(1,28)])"; which tesseract || true
python -c "from PIL import Image; import os for i in range(1,28): p=f'/tmp/workspace/case-review/pages/p{i:02d}_2_X2.jpg'; im=Image.open(p); im.thumbnail((1200,1600)); im.save(f'/tmp/workspace/case-review/pages/s{i:02d}.jpg',quality=60,optimize=True) print([(i,os.path.getsize(f'/tmp/workspace/case-review/pages/s{i:02d}.jpg')) for i in range(1,28)])"
python -c "import importlib.util as u; print('cv2',u.find_spec('cv2'));print('easyocr',u.find_spec('easyocr'));print('keras_ocr',u.find_spec('keras_ocr'));print('paddleocr',u.find_spec('paddleocr'));print('transformers',u.find_spec('transformers'))"; ls /usr/bin | sed -n '/ocr\|convert\|magick/p'
~/attachments/fd575d3b-15ee-4140-8348-0df0dae971b4
periorbital edema differential diagnosis
alcohol smoking head neck cancer
pip install --quiet rapidocr_onnxruntime && python -c "from rapidocr_onnxruntime import RapidOCR; print('ready')"
python -c "from rapidocr_onnxruntime import RapidOCR; import glob,os; o=RapidOCR(); fs=sorted(glob.glob('/tmp/workspace/case-review/pages/p*_2_X2.jpg')); out=[] for f in fs: r,_=o(f); out.append('\n===== '+os.path.basename(f)+' =====\n'+'\n'.join(x[1] for x in (r or []))) open('/tmp/workspace/case-review/ocr.txt','w').write('\n'.join(out)); print('done',len(fs))"
Give me differentials Be quick
Have you read the uploaded file??