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AI in Health Sciences & Academia

An Artificial Intelligence (AI) system [is] a machine-based system that can, for a given set of human-defined objectives, make predictions, recommendations, or decisions influencing real or virtual environments.

Organisation for Economic Co-operation and Development (OECD)

Seven use cases for AI, that can run in parallel with one another:

  1. Hyper-personalization - displaying relevant content in online searching; targeted marketing (e.g. Netflix suggested shows)
  2. Conversation and human interaction - e.g. chatbots for mental health care; Alexa, Siri, & Google Assistant
  3. Pattern and anomaly detection - detecting fraud; flagging purchases in unusual amounts or locations
  4. Recognition - facial/voice recognition; e.g. combine with anomaly detection to review photos of skin and provide potential diagnoses
  5. Goal driven systems - finding optimal solutions to specific problems; gaming (e.g. Deep Blue, the computer that beat the world chess champion in 1997)
  6. Predictive analytics and decision support - prediction about human behavior; weather forecasting
  7. Autonomous systems - able to interact with surroundings and achieve objectives with little to no human involvement (e.g. autonomous vehicles)

From Artificial Intelligence & Responsible Business Conduct, OECD

Large Language Models (LLM)

  • Very large "deep learning" AI models that are pre-trained using immense amounts of data
  • Incredibly flexible, can be used to consider billions of parameters to:
    • answer questions
    • complete sentences
    • summarize documents
    • translate languages
  • Demonstrate an ability to make predictions based on a small number of input/prompts
  • Can be used for generative AI to produce content based on human input/prompts

From What are Large Language Models (LLM)?, AWS