1.What are the stakeholders that should be involved in applying Machine Learning in symptom prediction? What are their roles and responsibilities?
= 1.1 Oncologists and Other Healthcare Professionals (Medical Expertise): Provide medical knowledge to guide model development and ensure the predictions align with clinical reality. Their role also includes ensuring ethical considerations in symptom management are addressed for patient safety.
1.2 Data Scientists (Machine Learning Expertise): Develop the model and ensure the machine learning algorithms are accurate, reliable, and technically robust.
1.3 Patients: Provide accurate information about their symptoms and experiences to improve the model’s accuracy. Once the model is launched, they can offer feedback on the effectiveness of the predictions.

2. What potential ethical considerations or challenges should researchers and clinicians keep in mind when developing and deploying machine learning models to predict cancer symptoms?
= 2.1 Ethical considerations: Researchers and clinicians should prioritize data privacy and ensure informed consent from patients. This will provide transparency in how patient data is used during the model’s development and application. Protecting patient privacy throughout the data collection, storage, and analysis phases is essential to maintaining trust and ethical integrity.
2.2 Challenges: A significant challenge is managing biased data. While more input data generally improves the reliability and accuracy of machine learning models, biased input data can lead to skewed predictions. In the worst-case scenario, it could lead to inaccurate predictions that may harm patients.