openmedical/registry
← registry

NNCPR

imported

software/nncpr

Practical Applications of Deep Learning: Classifying the most common categories of plain radiographs in a PACS using a neural network (NNCPR)

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

NNCPR project image
GitHub preview card for healthcAIr/NNCPR. Served by its origin, not stored here, and not covered by this registry’s licence.
record
Category
Software & Systems
Subcategory
unknown
License
Apache-2.0(osi)
Status
dormant
Maturity
deployed
Organization
healthcAIr
Country
unknown
Homepage
unknown
Documentation
unknown
Tags
classification · network · neural · nncpr · pacs · radiographs
Regulatory
unknown
built by · 1

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.

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.

  • PACmegneural

    MATLAB scripts for detecting and validating phase amplitude coupling (PAC) in electrophysiological data

  • SIFTneural

    SIFT is an EEGLAB-compatible toolbox for analysis and visualization of multivariate causality and information flow between sources of electrophysiological (EEG/ECoG/MEG) activity. It consists of a…

  • R package to do the Ligand Receptor Analysis Visualization

  • Network analysis and visualization of drug-drug interactions with NetworkX and Pyvis

  • Allocation optimization of patients during covid pandemic using real data from Brazil 2020-2022 period.

  • Visualization and analysis platform for metabolic data and network pattern recognition

sources
  1. api.github.com/repos/healthcAIr/NNCPR
    retrieved 2026-08-05 · via github-api

    Machine-imported from GitHub search. Last push 2020-09-15, 3 stars, license reported as Apache-2.0. Category and schematic were assigned by keyword heuristics and are unreviewed.

Not yet verified by a human. Correct this record →

machine-readable

/v1/entries/20.json→ .entries["nncpr"]

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