skin cancer classification Classification Dataset and Pre-Trained Model by Smart Healthcare Mnaagement

Images

9900 images

Explore Dataset

Here are a few use cases for this project:

Healthcare Diagnostics: Dermatologists can use the "skin cancer classification" model to supplement their diagnosis process, applying it to images of skin abnormalities to determine if they could be indicative of specific types of skin cancer like nv, mel, bkl, etc.
Telemedicine Applications: The model can be integrated into telemedicine platforms allowing users to upload images of suspicious skin patches for preliminary screening and classification of potential skin cancer, enhancing patient triage before visiting a specialist.
Educational Tools: Medical schools and training programs can use the model as an educational tool to train upcoming dermatologists on skin cancer types, demonstrating real-world detection and classification.
Mobile Health Apps: Health app developers can utilize the model in skin health monitoring applications, enabling users to routinely check and monitor skin abnormalities. Depending on the model's output, users can be prompted to visit a medical professional further for examination.
Pharmaceutical Research: The model could be used in clinical trials or drug research to monitor the effectiveness of skin cancer treatments over time, by classifying and comparing the cancer type before and after the trial period.

Trained Model API

This project has a trained model available that you can try in your browser and use to get predictions via our Hosted Inference API and other deployment methods.

Cite This Project

If you use this dataset in a research paper, please cite it using the following BibTeX:

@misc{
                            skin-cancer-classification-kjic2_dataset,
                            title = { skin cancer classification Dataset },
                            type = { Open Source Dataset },
                            author = { Smart Healthcare Mnaagement },
                            howpublished = { \url{ https://universe.roboflow.com/smart-healthcare-mnaagement/skin-cancer-classification-kjic2 } },
                            url = { https://universe.roboflow.com/smart-healthcare-mnaagement/skin-cancer-classification-kjic2 },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { sep },
                            note = { visited on 2024-05-10 },
                            }