openmedical/registry
← registry

ingbetic

imported

software/ingbetic

Ingredient to Sugar Level Estimation (from training in Python to edge deployment in JS/TS)

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

record
Category
Software & Systems
Subcategory
unknown
License
MIT(osi)
Status
dormant
Maturity
deployed
Organization
unknown
Country
unknown
Documentation
unknown
Tags
deep-learning · diabetes · edge-deployment · huggingface · nextjs
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.

  • MedFlow-V1huggingface

    MedFlow AI — FastAPI/React microservices for medical triage and imaging analysis with Google MedGemma (Gradio/API); Dockerized, analytics-ready, and suitable for demo/research use.

  • pillchecker-apihuggingface

    Medication interaction checker API (OpenMed + RxNorm + DrugBank)

  • druggpthuggingface

    DrugGPT: A GPT-based Strategy for Designing Potential Ligands Targeting Specific Proteins

  • A multi agent healthcare assistant system implemented using Python and Langgraph. The agents include icd10 code extractor, SOAP document generator and medical image report generator. This project…

  • OpenGPThuggingface

    A framework for creating grounded instruction based datasets and training conversational domain expert Large Language Models (LLMs).

  • ReportQLhuggingface

    Code and dataset for paper - Application of Deep Learning in Generating Structured Radiology Reports: A Transformer-Based Technique

sources
  1. api.github.com/repos/ziqinyeow/ingbetic
    retrieved 2026-08-05 · via github-api

    Machine-imported from GitHub search. Last push 2023-06-09, 6 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/46.json→ .entries["ingbetic"]

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