Corpus ID: 237439316

Melatect: A Machine Learning Model Approach For Identifying Malignant Melanoma in Skin Growths

@article{Meel2021MelatectAM,
  title={Melatect: A Machine Learning Model Approach For Identifying Malignant Melanoma in Skin Growths},
  author={Vidushi Meel and Asritha Bodepudi},
  journal={ArXiv},
  year={2021},
  volume={abs/2109.03310}
}
Malignant melanoma is a common skin cancer that is mostly curable before metastasis -when growths spawn in organs away from the original site. Melanoma is the most dangerous type of skin cancer if left untreated due to the high risk of metastasis. This paper presents Melatect, a machine learning (ML) model embedded in an iOS app that identifies potential malignant melanoma. Melatect accurately classifies lesions as malignant or benign over 96.6% of the time with no apparent bias or overfitting… Expand

Figures from this paper

References

SHOWING 1-10 OF 47 REFERENCES
An Overview of Melanoma Detection in Dermoscopy Images Using Image Processing and Machine Learning
TLDR
An overview of computerized detection of melanoma in dermoscopy images is provided and the various aspects of lesion segmentation are discussed, including the classification stage where machine learning algorithms are applied to the attributes generated from the segmented features to predict the existence of melanomas. Expand
Vision-Based Classification of Skin Cancer using Deep Learning
TLDR
This study aims to produce an inexpensive and fast computer-vision based machine learning tool that can be used by doctors and patients to track and classify suspicious skin lesions as benign or malignant with adequate accuracy using only a cell phone camera. Expand
The Development of a Skin Cancer Classification System for Pigmented Skin Lesions Using Deep Learning
TLDR
The classification accuracy of FRCNN was better than that of the dermatologists, and it is planned to implement this system in society and have it used by the general public, in order to improve the prognosis of skin cancer. Expand
Skin Cancer Detection: A Review Using Deep Learning Techniques
TLDR
A detailed systematic review of deep learning techniques for the early detection of skin cancer and how they are used to distinguish benign skin cancer from melanoma is presented. Expand
Early detection and treatment of skin cancer.
TLDR
Patients should be taught basic "safe sun" measures: sun avoidance during peak ultraviolet-B hours; proper use of sunscreen and protective clothing; and avoidance of suntanning. Expand
Visual inspection and dermoscopy, alone or in combination, for diagnosing keratinocyte skin cancers in adults.
TLDR
To determine the diagnostic accuracy of visual inspection and dermoscopy, alone or in combination, for the detection of BCC and cSCC, in adults, a comprehensive search of the following databases was undertaken. Expand
Deep Learning to Improve Breast Cancer Detection on Screening Mammography
TLDR
A deep learning algorithm is developed that can accurately detect breast cancer on screening mammograms using an “end-to-end” training approach that efficiently leverages training datasets with either complete clinical annotation or only the cancer status of the whole image. Expand
Assessment of Accuracy of an Artificial Intelligence Algorithm to Detect Melanoma in Images of Skin Lesions
TLDR
As the burden of skin cancer increases, artificial intelligence technology could play a role in identifying lesions with a high likelihood of melanoma. Expand
Survival rates of patients with metastatic malignant melanoma
TLDR
The influence of metastases distribution on the overall survival was examined and it was noticed that there were statistically significant differences between the risks of death of various groups of patients, depending on metastasis topography. Expand
Artificial intelligence and interpretations in breast cancer imaging
TLDR
This chapter focuses on the role of AI in breast cancer image interpretation, going beyond the initial use in computer-aided detection to include diagnosis, prognosis, response to therapy, and risk assessment, as well as in cancer discovery. Expand
...
1
2
3
4
5
...