Memory-Based Learning
IBM Is Teaching Watson To Interpret Medical Images
That could help them catch serious problems that are hard to see with the naked eye. A supercomputer could also act as a kind of second opinion, helping to confirm a doctor's suspicions about a somewhat unusual diagnosis. That, in turn, could cut down on redundant testing, which saves patients time, money and dangerous radiologic exposure.
IBM's Watson Gets Its First Piece Of Business In Healthcare
The old Watson that beat Ken Jennings. Now it can fit into a desk drawer. Thanks to a business partnership among IBM, Memorial Sloan-Kettering and WellPoint, health care providers will now be able to tap Watson's expertise in deciding how to treat patients. Pricing was not disclosed, but hospitals and health care networks who sign up will be able to buy or rent Watson's advice from the cloud or their own server. Over the past two years, IBM's researchers have shrunk Watson from the size of a master bedroom to a pizza-box-sized server that can fit in any data center.
The Case-Based Reasoning Group
Current research projects include projects to investigate the use of multiple case representation and indexing schemes in precedent-based CBR, the effect of high level reasoning goals on supporting CBR tasks and vice versa in a mixed paradigm blackboard-based architecture, the use of CBR for generation of retrieval strategies in the context of information retrieval, and the automatic selection of parameters for dynamic scheduling problems.
Case-Based (CBR) Creativity: SWALE project home page
We need heuristics for the intentional reminding of explanation patterns XP retrieval is the process of formulating questions to memory: we characterize an anomalous situation in terms of a set of indices, and ask what XPs in memory explain similar situations. When no answer is available, we must reformulate the question into one that we can answer. When no solution is directly available, people often fall back on asking standard questions that give background information. Answers to explanation questions like what physical causes underlie this event?, what special circumstances made the event happen now?, what motivates the actor of this surprising action?, how did the victim enable this bad event?, or what groups might the actor be trying to serve?, may suggest relevant factors that can be used as indices for XP retrieval. Though the XPs accessed in this way might not be directly applicable, it may be possible to adapt them. A creative system needs a set of explanation questions for gathering information, rules for selecting which questions to apply in a given situation, and rules for transforming them to fit.
The AI-CBR - 67 Steps & Blackout USA
One of life's harsh little truths is that there are unfortunately a lot of people living unfulfilling lives. There are so many twists and turns that make us deviate from our hopes and dreams, leading to an awful lot of compromise. It's impossible to just flip a switch and have it all change to whatever we're dreaming of, but there at least a few ways to finally take the reigns and hopefully chase down a little more fulfillment and happiness. One of our favorite resources for this is The 67 Steps by Tai Lopez. If you want to know more about it then The 67 Steps Rocks!
Artificial Neural Networks and Case-Based Reasoning Systems for Auditing
Audit sampling is selecting a group of items such as invoices for investigation to draw inferences about an account balance. Ratio analysis involves comparisons between two financial statement accounts such as current ratios and gross profit percentage. Reasonable tests involve using financial and nonfinancial data to estimate an account balance. An example would be multiplying items sold by price to determine expected revenue. However, there are audit engagement risks with current auditing techniques.
Exploring Synergies of Knowledge Management and Case-Based Reasoning
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The General Motors Variation-Reduction Adviser: Deployment Issues for an AI Application
The General Motors Variation-Reduction Adviser is a knowledge system built on case-based reasoning principles that is currently in use in a dozen General Motors Assembly Centers. This paper reviews the overall characteristics of the system and then focuses on various AI elements critical to support its deployment to a production system. A key AI enabler is ontology-guided search using domain-specific ontologies. Your use of this site constitutes acceptance of all of AAAI's terms and conditions and privacy policy.
CaBMA: Case-Based Project Management Assistant
We are going to present an implementation of an AI system, CaBMA, built on top of a commercial project management tool, MS Project. Project management is a business process for successfully delivering one-of-a kind products and services under real-world time and resource constraints. CaBMA (for: Case-Based Project Management Assistant) provides the following functionalities: (1) It captures cases from project plans. CaBMA adds a knowledge layer on top of MS Project to assist the user with his project management tasks. Your use of this site constitutes acceptance of all of AAAI's terms and conditions and privacy policy.
Tenth Anniversary of the Plastics Color Formulation Tool
Since 1994 GE Plastics has employed a case-based reasoning tool that determines color formulas which match requested colors. This tool, called FormTool, has saved GE millions of dollars in productivity and material (i.e. The technology developed in FormTool has been used to create an on-line color selection tool for our customers called ColorXpress Select. A customer innovation center has been developed around the FormTool software. Your use of this site constitutes acceptance of all of AAAI's terms and conditions and privacy policy.