Security News > 2024 > April > Overcoming GenAI challenges in healthcare cybersecurity

What are the key cybersecurity challenges in healthcare in the context of GenAI, and how can they be effectively addressed?

How do you see GenAI transforming healthcare operations and patient care, especially regarding efficiency and decision-making?

Given the sensitivity of healthcare data, what measures should be in place to ensure that GenAI innovations do not compromise patient privacy?

Anonymization and de-identification techniques that remove personally identifiable information from healthcare data before its use for GenAI training will help to ensure compliance with privacy regulations such as HIPAA and GDPR and lead to greater adoption and trust of GenAI tools in healthcare.

Historically, healthcare data has many built-in biases when it comes to race, ethnicity, and gender but bias in GenAI could result from bias in the training dataset, feature selection, data collection, labeling process, or even the model architecture itself.

The decision-making process of GenAI models should be transparent and explainable to healthcare providers and patients.

News URL

https://www.helpnetsecurity.com/2024/04/25/asaf-mischari-team8-health-genai-healthcare-risks/