# AI Clinics on Mobile (AICOM): Universal AI Doctors for the Underserved and Hard-to-Reach

arXiv: https://arxiv.org/abs/2306.10324 · HTML: https://mlsanity.com/paper/2306.10324/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 6 of its 37 references that are in the map.
- First posted on arXiv 17 Jun 2023.

## Builds on (most cited first, 6 of 6)

- [Language Models are Few-Shot Learners](https://mlsanity.com/paper/2005.14165/) (2020)
- [Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding](https://mlsanity.com/paper/1510.00149/) (2015)
- [Large Language Models Encode Clinical Knowledge](https://mlsanity.com/paper/2212.13138/) (2022)
- [A Survey of Model Compression and Acceleration for Deep Neural Networks](https://mlsanity.com/paper/1710.09282/) (2017)
- [AICOM-MP: an AI-based Monkeypox Detector for Resource-Constrained Environments](https://mlsanity.com/paper/2211.14313/) (2022)
- [Autonomous Mobile Clinics: Empowering Affordable Anywhere Anytime Healthcare Access](https://mlsanity.com/paper/2204.04841/) (2022)

## Abstract (arXiv)

This paper introduces Artificial Intelligence Clinics on Mobile (AICOM), an open-source project devoted to answering the United Nations Sustainable Development Goal 3 (SDG3) on health, which represents a universal recognition that health is fundamental to human capital and social and economic development. The core motivation for the AICOM project is the fact that over 80% of the people in the least developed countries (LDCs) own a mobile phone, even though less than 40% of these people have internet access. Hence, through enabling AI-based disease diagnostics and screening capability on affordable mobile phones without connectivity will be a critical first step to addressing healthcare access problems. The technologies developed in the AICOM project achieve exactly this goal, and we have demonstrated the effectiveness of AICOM on monkeypox screening tasks. We plan to continue expanding and open-sourcing the AICOM platform, aiming for it to evolve into an universal AI doctor for the Underserved and Hard-to-Reach.