However, the article also raises concerns about regulatory oversight, data security, and the need for robust cybersecurity measures to protect patient data. It mentions the collaboration between health providers, governments, and regulatory agencies in developing guidelines for AI/ML-based medical devices. The author concludes by stating that as technology advances, it will be used more frequently to achieve successful patient outcomes.
Key takeaways:
- Artificial intelligence (AI) and machine learning (ML) are being used in healthcare for diagnosis and treatment recommendations, patient engagement, and administrative activities. They can predict patient outcomes and recommend treatments based on a patient's electronic health record (EHR).
- AI and ML are also being used in wearable devices to predict and prevent health issues. For example, Chronolife pairs with Garmin devices to monitor over 20 health indicators and predict critical medical events.
- Chatbots, another application of AI, can diagnose health issues quickly and effectively, allowing patients to seek medical advice without leaving their homes. The market size for chatbots is predicted to reach $943 million by 2030.
- As the use of AI and ML in healthcare grows, concerns over regulatory oversight and data security are also increasing. Health providers and governments are collaborating to develop guidelines for good practice in developing AI/ML-based medical devices, and organizations are taking measures such as data encryption and two-factor authentication to secure data.