Artificial intelligence in healthcare: opportunities and challenges | Navid Toosi Saidy | TEDxQUT

Artificial intelligence (AI) can save lives and improve Healthcare by personalizing care, making hospitals more efficient, and providing accurate decision-making tools.

• AI educates computer models using complex data sets to make decisions or predict outcomes.
• AI models help Doctors learn from patients with similar conditions or genetic information to make informed decisions about diagnosis and treatment.
• AI is being used to streamline Cancer diagnosis by consolidating information from blood tests, imaging, and genetic data to provide accurate predictions of diagnosis, treatment options, and prognosis.
• Existing Regulation frameworks are not designed for AI-based software as a medical device, which can learn and evolve over time, leading to potential challenges in implementation.
• Emerging Regulation frameworks are being proposed to ensure transparency, ongoing monitoring, and representative training data for AI algorithms in Healthcare.
• Developers need to ensure that AI models are trained on diverse and representative data sets to avoid bias and provide accurate results for all populations.
• New regulatory frameworks need to be established in consultation with AI developers, Healthcare practitioners, policy advisers, and patients to ensure the successful implementation of AI in Healthcare.

Researchers/sources featured

• Navid Toosi Saidy