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Artificial intelligence an introduction.pptx
- 1. ARTIFICIAL INTELLIGENCE: an introduction DR.SHREEPAL JAIN pediatric & fetal cardiologist b. j. wadia hospital for children, mumbai
- 2. What is AI? artificialintelligence is the science of making machines do things that would require intelligence if done by humans …….Marvin Minsky
- 3. history Alan Turing, Britishmathematician and computer scientist - progenitor of AI Decoding the secret messages sent via german enigma machine during WW-II using machine intelligence
- 4. history CAPTCHA - developedby turing for differentiating humans from machines (bots)
- 5. history AI - coinedby stanford scientist John McCarthy at the dartmouth conference in 1956. Frank Rosenblatt (1958) - the perceptron a 3-layer structure - early precursor of the artificial neural network and present day deep learning
- 6. history of aiin medicine earliest work - 1960s edward shortliffe - innovative heuristic programming project MYCIN
- 7. history of aiin medicine Artificial intelligence failure: lack of favourable work flow logistics lack of integration to accommodate the clinicians, and, also due to expectations that were unrealistically high but never met.
- 8. history of aiin medicine renewed focus on data mining and machine learning - 1990’s IBM supercomputer DEEP BLUE defeated Gary Kasparov in chess (1997) Three main factors heralding the new AI era: increasingly large volumes of available data that requires new computational methodologies (Big Data), the escalating capability of computational power and cloud computing the emergence of machine and deep learning
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- 10. A, B, C,D of AI Algorithms: sets of steps to accomplish certain tasks calculation data processing automated reasoning e.g. NASA’s solar panel operation on ISS
- 11. A, B, C,D of AI Big Data: escalated in such exponential way to make conventional data processing applications inadequate 4 V’s: Volume Variety Velocity Veracity
- 12. A, B, C,D of AI Cognitive computing: machine learning supervised learning unsupervised learning reinforcement learning
- 13. A, B, C,D of AI deep learning convoluted neural network recurrent neural network natural language processing Internet of things (IoT)
- 14. Types of AI typedefinition level of human involvement examples assisted system providing & automating repetitive tasks little or none UR ROBOTS for blood work augmented humans & machines together make decisions some or high IBM WATSON for oncology autonomous decisions made by adaptive intelligent systems autonomously little or none IDx-DR diagnosing retinal images
- 15. current status ofai in cardiology clinical domain: digital stethoscope imaging domain: ecg analysis echo imaging ct/ mr imaging intensive care domain
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- 25. AI in intensivecare big data machine learning pattern recognition deep learning or rnn to analyse & make decisions
- 26. To conclude ai ishere and we cannot escape it imaging and data rich fields will be significantly impacted ai will take away jobs…..unlikely innovations need to be accepted early in clinical practice…..before they make us primitive (e.g. nokia, kodak)