Summary of 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
Notable Quotes
— 00:16 — « But I’m here to tell you that AI can actually save lives »
— 00:25 — « AI is helping us personalize the delivery of care, make hospitals more efficient, and improve access to health care by providing accurate decision-making tools. »
— 01:27 — « I want to talk about how we are starting to use AI for delivering care to cancer patients. »
— 01:58 — « This involves feeding an AI model data from the patient’s blood tests, X-ray images of the suspected lesions, as well as genetic information from a tissue biopsy. »
— 06:01 — « that the training data used for these algorithms are representative of the entire human population. »
Category
Science and Nature