mlsanityData to 14 Oct 2026

Mobile Imaging Solutions for Medical Diagnosis: Trends and Applications

arXiv 2609.24814 ↗First posted 21 Sep 2026cs.CV cs.AI cs.LGcited by 0

Not on the map. Why?

Abstract (arXiv)

Advances in processing power, camera technologies, and mobile image analysis have made smartphones and other mobile devices, such as laptops, increasingly suitable for medical diagnosis and healthcare applications. Researchers have developed low-cost solutions for the early detection and monitoring of various health conditions, including eye and ENT diseases, malnutrition, heart rate variability, skin and oral conditions, and injuries, using images captured by non-medical devices such as smartphones and webcams. This survey examines existing research on mobile image-based medical diagnosis, with an emphasis on its potential to enable low-cost and accessible healthcare. We comparatively analyze state-of-the-art solutions across different healthcare application categories, examining their advantages and limitations. Based on this analysis, we identify desirable characteristics of mobile image-based diagnostic tools and highlight areas where existing approaches have made progress as well as areas requiring further research. We also discuss application-specific and common challenges and outline directions for future research. Overall, this study provides a comprehensive overview of mobile image-based healthcare solutions and their potential to support low-cost disease diagnosis and monitoring, particularly for underserved populations in remote and resource-constrained settings.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 7 of its 140 references that are in the map. First posted on arXiv 21 Sep 2026.

Builds on

7 of 140 references.

References · 7

  1. 2014Very Deep Convolutional Networks for Large-Scale Image Recognitioncited by 15,364
  2. 2017A Unified Approach to Interpreting Model Predictionscited by 6,555
  3. 2016"Why Should I Trust You?": Explaining the Predictions of Any Classifiercited by 5,070
  4. 2017A Survey on Deep Learning in Medical Image Analysiscited by 1,186
  5. 2020OralCam: Enabling Self-Examination and Awareness of Oral Health Using a Smartphone Cameracited by 3
  6. 2022Skin Cancer Diagnostics with an All-Inclusive Smartphone Applicationcited by 2
  7. 2020A Smartphone-based System for Real-time Early Childhood Caries Diagnosiscited by 1

Built on by

Not cited yet.