Chapter 10 Clinical Implication
10.1 ML in clinical settings
We could have the following uses of ML methods in the clinical settings:
- prescreen patients to identify high-risk patient pool.
- warn patients about imminent risk
- helps manage clinical workload
- help diagnose a disease better with high accuracy
- could be based on radiology or pathology images
- could prevent mis-diagnose by giving a second opinion
- could indicate suspicious regions, assisting clinicians to focus on the most important considerations
- Monitoring vulnerable patients
- monitoring devices (e.g., fall detection)
- ethical, moral and transparency considerations