# albarqouni/Deep-Learning-for-Medical-Applications

Deep Learning Papers on Medical Image Analysis

Repository: https://github.com/albarqouni/Deep-Learning-for-Medical-Applications
Canonical: https://ross.abutalabs.com/products/deep-learning-for-medical-applications
Language: TeX
License: GPL-3.0
License Family: copyleft
Topics: deep-learning, medical-imaging, medical-informatics, awesome-list
Last push: 2022-04-01T08:51:47+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3462, "days_push": 1615, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1608, forks 503 (observed 2026-08-28T04:05:10.683191+00:00)

## What it is
A curated awesome-list of deep learning papers on medical image analysis, organized by technique (CNN, RNN, GAN, autoencoders) and medical application (segmentation, classification, detection, registration). Papers are annotated with metadata like imaging modality and clinical database.

## Use cases
- find deep learning papers on medical image segmentation
- get a starting reading list for deep learning in medical imaging
- find papers on MRI or CT analysis using CNNs
- survey GAN applications in medical imaging
- find peer-reviewed papers on tumor detection and localization
- research deep learning for histopathology image classification

## When to choose
- starting research in deep learning for medical applications
- building a literature review on medical image analysis
- looking for curated, peer-reviewed papers with modality metadata

## When to avoid
- you need runnable code or datasets rather than paper references
- you need up-to-the-minute papers, as the list is no longer actively updated

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: deep-learning, machine-learning, computer-vision, image-processing
- domain: deep-learning, healthcare, computer-vision, machine-learning, awesome-lists
- platform: cross-platform
- tags: awesome-list, medical-imaging, papers, research, bibliography

## Member repositories
- albarqouni/Deep-Learning-for-Medical-Applications (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:10.683191+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T03:51:20.588547+00:00, confidence not recorded.
  - readme: https://github.com/albarqouni/Deep-Learning-for-Medical-Applications (fetched 2026-08-28T04:05:10.683191+00:00, sha 21d2fb42be06)
- Data as of 2026-08-30T08:39:29.467469+00:00.