Summary of Enhancing Cancer Diagnosis with Explainable & Trustworthy Deep Learning Models, by Badaru I. Olumuyiwa et al.
Enhancing Cancer Diagnosis with Explainable & Trustworthy Deep Learning Models
by Badaru I. Olumuyiwa, Anh Han, Zia U. Shamszaman
First submitted to arxiv on: 23 Dec 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary Medium Difficulty Summary: This research introduces an innovative approach to cancer diagnosis and prediction using explainable Artificial Intelligence (XAI) and deep learning techniques. The study develops an AI model that provides precise outcomes and clear insights into its decision-making process, addressing the “black box” problem of deep learning models. Employing XAI techniques enhances interpretability and transparency, building trust among healthcare professionals and patients. The approach leverages neural networks to analyze extensive datasets, identifying patterns for cancer detection. This model has the potential to revolutionize diagnosis by improving accuracy, accessibility, and clarity in medical decision-making, possibly leading to earlier detection and more personalized treatment strategies. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Low Difficulty Summary: This research helps make it easier to diagnose cancer using special computers called AI. Cancer is a big problem that causes many deaths each year. Traditional methods are often expensive, not very accurate, or take too long. The new approach uses something called XAI and deep learning to create a model that can accurately detect cancer and explain why it made certain decisions. This helps doctors and patients understand the diagnosis better. The model could make it easier to diagnose cancer earlier and develop more personalized treatments. It could also help people in poor countries get access to good diagnostic tools, making healthcare fairer globally. |
Keywords
» Artificial intelligence » Deep learning
