RANZCR-CLiP
importedsoftware/ranzcr-clip
Multi-label CV classification with 87% accuracy in detecting correct catheter placement in COVID-19 patient chest x-rays under the Royal Australian and New Zealand College of Radiologists Catheter…
Machine-generated from the listed sources and not yet reviewed by a human.
- Category
- Software & Systems
- Subcategory
- unknown
- License
- MIT(osi)
- Status
- dormant
- Maturity
- deployed
- Organization
- unknown
- Country
- unknown
- Homepage
- unknown
- Repository
- github.com/YasPHP/RANZCR-CLiP
- Documentation
- unknown
- Tags
- catheter-detection · computer-vision · covid-19 · efficientnetb7 · kaggle · keras-tensorflow · radiology · ranzcr
- Regulatory
- unknown
Top contributors by commit count, from the project’s public repository. Avatars are served by their origin, not stored here. To be removed from this list, open an issue.
Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.
- chest-xray-pneumonia-detection-aicomputer-vision · keras-tensorflow
AI-powered chest X-ray pneumonia detection with 86% accuracy and 96.4% sensitivity, validated on an independent (cross-operator) cohort of 485 pediatric samples. Built with TensorFlow & FastAPI.
- Glands-detectioncomputer-vision · keras-tensorflow
🧠 A deep learning algorithm based on convolutional neural networks to detect glandular cells in digitalized biopsies of the prostate.
- COVID-19-Scannercomputer-vision · covid-19 · radiology
This model is meant to help triage patients (prioritize certain patients for testing, quarantine, and medical attention) that require diagnosis for COVID-19. This model is not meant to diagnose…
- Skin-Cancer-Classification-using-Deep-Learningcomputer-vision · keras-tensorflow
Classify Skin cancer from the skin lesion images using Image classification. The dataset for the project is obtained from the Kaggle SIIM-ISIC-Melanoma-Classification competition.
- mRNA-Vaccine-Degradation-Predictioncovid-19 · kaggle
mRNA Vaccine Degradation Prediction using Deep Learning
- ct-net-modelscomputer-vision · radiology
Machine learning models for multi-organ, multi-disease prediction in chest CT volumes. From paper Draelos et al. "Machine-Learning-Based Multiple Abnormality Prediction with Large-Scale Chest…
- api.github.com/repos/YasPHP/RANZCR-CLiPretrieved 2026-08-05 · via github-api
Machine-imported from GitHub search. Last push 2021-05-09, 4 stars, license reported as MIT. Category and schematic were assigned by keyword heuristics and are unreviewed.
Not yet verified by a human. Correct this record →
/v1/entries/46.json→ .entries["ranzcr-clip"]
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