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rl-medical

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software/rl-medical-gml16

Communicative Multiagent Deep Reinforcement Learning for Anatomical Landmark Detection using PyTorch.

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rl-medical project image
GitHub preview card for gml16/rl-medical. 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
active
Maturity
deployed
Organization
unknown
Country
unknown
Documentation
unknown
Tags
deep-learning · deep-reinforcement-learning · healthcare · landmark-detection · machine-learning · multiagent-reinforcement-learning · reinforcement-learning
Regulatory
unknown
built by · 6

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.

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    Learning representations for RL in Healthcare under a POMDP assumption

  • paccmann_generatordeep-reinforcement-learning

    Generative models for transcriptomic-driven or protein-driven molecular design (PaccMann^RL).

  • armscan_envreinforcement-learning

    A Gymnasium environment and RL algorithms for navigation on human arms using ultrasound/MRI

  • CellTRIPreinforcement-learning

    CellTRIP, Inferring virtual cell environments using multi-agent reinforcement learning for spatiotemporal trajectory interpolation, imputation, and perturbation

  • EHR-RLreinforcement-learning

    The potential for the use of AI is dramatic especially as it can assist family clinicians who are usually overloaded with patients to make better choices for treatment of their type 2 patients in…

sources
  1. api.github.com/repos/gml16/rl-medical
    retrieved 2026-08-05 · via github-api

    Machine-imported from GitHub search. Last push 2026-05-01, 92 stars, license reported as Apache-2.0. Category and schematic were assigned by keyword heuristics and are unreviewed.

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machine-readable

/v1/entries/47.json→ .entries["rl-medical-gml16"]

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