Please enable JavaScript.
Coggle requires JavaScript to display documents.
AI Course Materials- From Artificial intelligence Basics - Coggle Diagram
AI Course Materials- From Artificial intelligence Basics
Data
Structured Data Storage
Stored in a Spreadsheet
Morality Reviews and Code Blue Reviews
Stored in a relational database
Complication Rates for CHF, AMI, VTE
Unstructured Data, no predefined formatting
Nursing Notes, Progress notes, EPIC "Secure Messaging Files" in Healthcare
Semi-Structured Data
Tag lines to help with compiling data
BIG DATA
National Stroke Registry
AMI and Heart Failure Registry from the National Heart Center
Machine Learning
Data Order
Choose a Model
Train a Model
Evaluate a Model
Fine tune the model
Robotic Process Automation (RPA): Easier path to AI.
RPA: Low code visual drag and drop systems.
Unattended, completely automated
RDA: RPA helps an employee with a job or task
Benefits:
High customer satisfaction
lower error rates
improved compliance
easier integration with legacy systems
Drawbacks:
Difficulty with adaption to changes
issues with virtualized apps
Resistance
Center of Excellence Teams implement this
Natural Language Processing (NLP) allows computers to understand people
Chat boxes: communication
Lots of work that still needs to be done.
2 Steps:
Cleaning and reprocessing the text
Understanding and generating language
Text must be converted to form analysis
Stemming: the process of reducing words into its root.
Lemmatization: finding similar roots
Understanding:
Tagging speech
chunking
Topic Modeling
Physical Robots
High costs
Two types:
Customer Robots
Still in initial stages of development
Industrial Robets
Security Risk Factors
Intelligent robots have challenges need to create a physical system
Super complicated to develop
Ways to operate
Telerobot: controlled by humans
Autonomous robot, based on AI Systems
Slow process
Implementation of AI
Requires great care.
Ways to use AI in companies:
vendor software application
off the shelf models still require work
inhouse model
EDUCATION KEY PART
know the risks
Process Review for implementation
identify a problem
put together a team
find the right tools and platform
Create an AI Model
Deploy and monitor
The Future of AI
Drug Discovery
Healthcare advacements
Prescription Medications
Development
Generic Drug/Brand name
Automobiles
Self Driving
Monitors
Sensors
Video Cameras
Computers
Weaponizing AI
Global Leaders taking advantage of advancements
Enormous amounts of data
Drones and warefare
THE FUTURE IS AI
Deep Learning
Subfield of Machine Learning
Allows for Processing data
Find Relationships
Finding Patterns
Good Job at reflecting the real world
RNN: processes the input, prior inputs across time.
ANN: Artificial neural network: includes units that have weights and are used to predict values in an AI Model