CPP2005 an introduction to artificial intelligence in health care

Question 1

what is artificial intelligence?

Answer 1

Artificial intelligence is the simulation of human intelligence processes by machines, especially computer systems. Specific applications of AI include expert systems, natural language processing, speech recognition and machine vision

Question 2

what is machine learning?

Answer 2

a type of AI
the use and development of computer systems that are able to learn and adapt without following explicit instructions, by using algorithms and statistical models to analyse and draw inferences from patterns in data

Question 3

what is deep learning?

Answer 3

a type of machine learning
based on artificial neural networks in which multiple layers of processing are used to extract progressively higher level features from data

Question 4

what can AI be used for in healthcare?

Answer 4

• predicting disease/mortality
• picking up patterns in genetics or histology or symptoms and classifying for disease

Question 5

what are 5 potential problems with AI to do with data?

Answer 5

• data divide
• digital divide
• data owenership
• data quality
• data standards

Question 6

what is digital divide?

Answer 6

• not everyone has access to digital means
• affordability and knoweledge

Question 7

what is data divide?

Answer 7

• even now there is still not an accurate representation of all ethinicities, genders, ages, religions, sexuality in scientific studies

Question 8

what is data ownership?

Answer 8

• who has access to the data
• who can store and share personal data
• confidentiality

Question 9

what is data quality?

Answer 9

• cannot release a technology into healthcare if it does not have sufficient accuracy and efficiency
• high stakes

Question 10

what are the 3 steps of reviews of research?

Answer 10

• development questions
• validation questions
• impact questions

Question 11

what is AI in healthcare missing at the moment which means it cannot be 100% used?

Answer 11

• training = not enough resources to train enough healthcare staff how to use AI machinery
• transparency = too many digital software companies have affiliations and other interests when developing AI = may rush/ not pay attention to important thing like patient data protection = they are not healthcare professionals = have to be honest about everything
• clinical credibility = not enough supportive evidence and data to back up AI