AI-driven diagnostic tools typically follow a multi-step process. First, they collect and preprocess data, which may include medical images (like X-rays, CT scans, or MRIs) and patient history. Next, the data is analyzed using sophisticated algorithms trained on large datasets. These algorithms can identify patterns and anomalies indicative of cancer. Finally, the AI system provides a diagnosis or a probability score, which can be reviewed by a healthcare professional.
