1. The stakeholders that should involves in applying machine learning in symptoms prediction can be many professionals such as physician nurses pharmacists radiologist depends on which objective that machine learning will be doing for. In the study, for example, when focusing on the cancer symptom predictions in nursing field, by utilizing model predictions, nurses can anticipate and manage symptoms, thus enhancing personalized care plans. Furthermore, continuous monitoring of patient symptoms in real-time, using ML insights, enables nurses to make timely interventions, ultimately improving patient outcomes.
2. When developing and deploying machine learning models for predicting cancer symptoms, researchers and clinicians must ensure data privacy and security, obtaining informed consent, and mitigating biases in training data are crucial to protect patient rights and ensure fairness. Models must be transparent and explainable to gain the trust of clinicians and patients, with clear accountability for their predictions. Model validation is necessary to maintain accuracy across diverse populations. When it comes to human life, if using the low accuracy ML model with poor accountability, can significantly risk patients’ lives.