Early Diagnosis of Lyme Disease by Recognizing Erythema Migrans Skin Lesion from Images Utilizing Deep Learning Techniques

Sk Imran Hossain

IJCAI 2022poster1 citations

Early Diagnosis of Lyme Disease by Recognizing Erythema Migrans Skin Lesion from Images Utilizing Deep Learning Techniques

Abstract

Lyme disease is one of the most common infectious vector-borne diseases in the world. We extensively studied the effectiveness of convolutional neural networks for identifying Lyme dis-ease from images. Our research contribution includes dealing with lack of data, multimodal learning incorporating expert opinion elicitation, and automation of skin hair mask generation.

Machine Learning (ML): GeneralComputer Vision (CV): General

BibTeX

@inproceedings{ijcai2022p830,
  title     = {Early Diagnosis of Lyme Disease by Recognizing Erythema Migrans Skin Lesion from Images Utilizing Deep Learning Techniques},
  author    = {Hossain, Sk Imran},
  booktitle = {Proceedings of the Thirty-First International Joint Conference on
               Artificial Intelligence, {IJCAI-22}},
  publisher = {International Joint Conferences on Artificial Intelligence Organization},
  editor    = {Lud De Raedt},
  pages     = {5855--5856},
  year      = {2022},
  month     = {7},
  note      = {Doctoral Consortium},
  doi       = {10.24963/ijcai.2022/830},
  url       = {https://doi.org/10.24963/ijcai.2022/830},
}