Are There Any Challenges in Implementing AI for Cancer Diagnostics?
Despite its potential, there are several challenges in implementing AI for cancer diagnostics:
Data quality: AI algorithms require high-quality, annotated data for training, which can be difficult to obtain. Regulatory hurdles: Ensuring AI tools meet regulatory standards for safety and efficacy is complex. Integration with existing systems: Integrating AI into current healthcare infrastructure can be challenging. Ethical concerns: Issues related to data privacy, bias, and decision transparency need to be addressed.
