Explainable artificial intelligence (XAI) for exploring spatial variability of lung and bronchus. Publicado originalmente en Short. Sweet. Valuable..
Image created with DALL-E 3 by the author
Traditionally, AI in healthcare has been a ‘black box’, providing diagnosis or treatment recommendations without a clear explanation.
However, Explainable AI (XAI) is changing this narrative, especially in cancer care where understanding ‘why’ is as important as ‘what’.
XAI refers to artificial intelligence systems designed to provide understandable explanations of their operations, decisions, and results.
Traditional vs Explainable AI | Source
Its core objectives include:
- Transparency
- Interpretability
- Trust and Confidence
Why do we need XAI? Consider the case of lung cancer, the leading cause of cancer-related deaths globally.
AI systems have been a game-changer in assisting and detecting this type of disease in CT scans with surprisingly high accuracy.
Lung cancer detection with AI | Source
However, XAI takes this one step further by explaining what´s behind its diagnosis and highlighting specific patterns in the lung tissue**,** providing oncologists with insights into the analytical process.
Explainable artificial intelligence (XAI) for exploring spatial variability of lung and bronchus… Machine learning (ML) has demonstrated promise in predicting mortality; however, understanding spatial variation in…
Okey, but if the algorithm is working who cares about how?
Let´s see a practical example:
Imagine a doctor using an AI system to screen for lung cancer using patient CT scans. The AI algorithm indicates that a patient is at high risk of lung cancer. However, it doesn’t provide any explanation for its conclusion.
The doctor finds challenging to understand this AI-generated decision.
He faces several issues:
- Uncertainty in decision-making: The doctor is hesitant to make a critical decision, based on an unexplained assessment.
- Difficulty in communicating with the patient: He struggles to explain to the patient why the AI has suggested a high risk of cancer.
- Lack of trust in the AI system: Without clear explanations, the doctor finds it hard to trust the AI’s assessment.
Confused doctor | Source