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SYSTEM ONLINE · 02 MODELS REGISTERED · PACS READY
Praxic MedAgent // Clinical Computer Vision Deck

Two Screening Cores.
One Deterministic Clinical Pipeline.

MedAgent pairs verified medical knowledge retrieval with deep convolutional and YOLO11 classifiers, ensuring that every flagged finding arrives with structured visual telemetry, morphological metrics, and evidence-backed triage support.

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Protocol Interlock // Licensed Physician Verification Required

Praxic MedAgent functions strictly as a computational triage and screening decision-support aid. Outputs must be independently verified by a licensed medical practitioner prior to clinical decision-making. Praxic Intelligence assumes no liability for independent clinical outcomes.

Hands-On Telemetry Deck

Registered Diagnostic Models

Interact with the live clinical viewport: scrub CT scan slices, adjust window presets, and explore Bethesda cytology classifications.

ROI · 8.2mm (LUL)
SLICE 32/64
-640 HU
WINDOW: LUNG (W:1500 L:-600)
RISK SCORE: 88.4% [MALIGNANT ROI]
SCRUB SLICES:
Model 01 — Thoracic Low-Dose CT Live Inference Demo

Lung Cancer Screening & Nodule Tracking

Parses thin-slice low-dose CT series for suspicious pulmonary nodules, scores volumetric malignancy risk, and longitudinal scan doubling time to triage patient queues with maximum clinical precision.

  • ✓ Sub-millimeter volumetric nodule detection on low-dose thoracic CT
  • ✓ Malignancy probability scoring calibrated to Fleischner Society guidelines
  • ✓ Longitudinal registration against prior scans to calculate doubling time
  • ✓ Seamless DICOM / PACS integration with radiologist review queue
Input Modality
Low-Dose CT (DICOM)
Output Payload
3D Nodule Map + Risk Score
Deployment Stage
Active Clinical Demo
Launch Interactive DICOM Viewer Deploy In Hospital
HSIL · ATYPIA
FIELD 03/40 [400× LBC]
CLASSIFICATION: HSIL
STAIN: PAPANICOLAOU
N:C RATIO: 0.72 [HIGH]
BETHESDA SPECTRUM:
Model 02 — Cervical Cytology Active Validation

Cervical Cytology Bethesda Classification

High-Grade Squamous Intraepithelial Lesion (HSIL). High nuclear-to-cytoplasmic (N:C) ratio, coarse clumped chromatin, and irregular nuclear contours flagged across liquid-based cytology slides.

  • ✓ Slide-level multi-magnification triage across Pap smear & LBC preparations
  • ✓ Bethesda System-aligned grading from ASC-US, LSIL, to high-grade HSIL
  • ✓ Automated nuclear pleomorphism and hyperchromasia morphology measurement
  • ✓ Pathologist-in-the-loop audit view for accelerated secondary screening
Input Modality
Cytology Slide (WSI / LBC)
Output Payload
Bethesda Classification
Development Stage
Clinical Validation
View Cytology Prototype Deploy In Lab
Peer-Reviewed Research Grounding

Unifying Adult and Pediatric Domains: Multi-Dataset Deep Learning for Fracture Classification

Author: MD Saib Hossain (Founder & CEO, Praxic Intelligence) Conference: IEEE ICCIT 2025 DOI: 10.1109/ICCIT64616.2025.11491681

Praxic's clinical computer vision systems are directly grounded in academic research. Our published work at IEEE ICCIT 2025 demonstrates multi-domain generalization techniques across pediatric and adult radiology datasets, eliminating cross-demographic distribution drift and ensuring robust diagnostic reliability across diverse clinical populations.

Read on IEEE Xplore Record Google Scholar Profile