Diabetes_Research
importedsoftware/diabetes-research
Neural Networks for predicting diabetes from Fingerprints.
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/Sid2697/Diabetes_Research
- Documentation
- unknown
- Tags
- artificial-neural-networks · convolutional-neural-networks · diabetes · fingerprint · residual-neural-network
- 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.
- brain-computer-interfacingartificial-neural-networks
🧠 Brain-Computer Interfacing bootcamp course + projects @ Saturdays.AI (BCI + AI)
- MI-EEG-1D-CNNartificial-neural-networks
A new approach based on a 10-layer one-dimensional convolution neural network (1D-CNN) to classify five brain states (four MI classes plus a 'baseline' class) using a data augmentation algorithm and…
- e3fpfingerprint
3D molecular fingerprints
- Rcpifingerprint
💊 Molecular informatics toolkit with integration of bioinformatics and cheminformatics tools for drug discovery
- Development of software and algorithms of parallel learning of artificial neural networks…artificial-neural-networks
The object of research is to parallelize the learning process of artificial neural networks to automate the procedure of medical image analysis using the Python programming language, PyTorch…
- airpiconvolutional-neural-networks
AI-assisted rapid phase imaging for 4D-STEM
- api.github.com/repos/Sid2697/Diabetes_Researchretrieved 2026-08-05 · via github-api
Machine-imported from GitHub search. Last push 2018-05-10, 3 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/30.json→ .entries["diabetes-research"]
Entries are sharded 64 ways by a stable hash of the id, so a consumer can find any record without an index.