openmedical/registry
← registry

DenseNet-MURA-PyTorch

imported

data/densenet-mura-pytorch

Implementation of DenseNet model on Standford's MURA dataset using PyTorch

Machine-generated from the listed sources and not yet reviewed by a human.

DenseNet-MURA-PyTorch project image
GitHub preview card for pyaf/DenseNet-MURA-PyTorch. Served by its origin, not stored here, and not covered by this registry’s licence.
record
Category
Data & Standards
Subcategory
unknown
License
MIT(osi)
Status
dormant
Maturity
deployed
Organization
unknown
Country
unknown
Documentation
unknown
Tags
densenet · exploratory-data-analysis · mura-dataset · pytorch · radiology · standford-ml-group
Regulatory
unknown
similar by tags

Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.

  • DeepRadiologymura-dataset · radiology

    Source code for Microsoft Code Fun Do Hackathon organized at IIT (BHU)

  • A Combined ResNet-DenseNet Architecture with ResU Blocks (ResU-Dense) for 12-lead ECG Abnormality Classification

  • nn-common-modulesdensenet · pytorch

    Pytorch Implementations of Common modules, blocks and losses for CNNs specifically for segmentation models

  • medical-image-captioningpytorch · radiology

    Medical Image Captioning with ViT-Base + Phi-2 + LoRA on ROCOv2 radiology dataset

  • Created an interactive Power BI dashboard to analyze hospital visitor data, using DAX for insights into patient demographics and service usage to enhance efficiency and satisfaction. The project…

  • Deep CNN for performing 3D super resolution on CT/MRI scans

sources
  1. api.github.com/repos/pyaf/DenseNet-MURA-PyTorch
    retrieved 2026-08-05 · via github-api

    Machine-imported from GitHub search. Last push 2018-06-15, 78 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 →

machine-readable

/v1/entries/31.json→ .entries["densenet-mura-pytorch"]

Entries are sharded 64 ways by a stable hash of the id, so a consumer can find any record without an index.