The INFORMS Analytics+ Conference showcased how companies are turning advanced analytics and AI into measurable operational results
In most emergency departments, beds are a hot commodity. But some patients don’t actually need a bed for their treatment – and accurately identifying those people is a low-lift but effective way to increase efficiency without sacrificing care quality, finds a study recently published in the journal Management Science.
The researchers developed a simple decision tree, informed by mathematical and machine learning models, to help staff decide whether a patient truly needs a bed or can be routed to a “vertical processing pathway” – that is, an area where they can be treated sitting up. Many hospitals already have such an area but don’t necessarily have a systematic way to decide which patients are treated there.
The artificial intelligence (AI) boom has ignited the demand for data centers. Goldman Sachs predicts a doubling of the power demand to run the data centers in just two years.
Generative AI tools such as ChatGPT, Gemini, and Preplexity require a significant amount of computing power to train large language models so they are able to answer user queries coming from the average person who is doing a search about basketball game statistics to investment bankers who are looking for nuggets of information that will help them invest in high return stocks.
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Sweeping tariff threats from the United States have been put on hold once again, and Saskatchewan businesses are taking a short breath. Nearly $30 billion in Canadian goods were about to be hit by a 50 per cent tariff, but the U.S. government extended the deadline and offered hope of a final deal on the way.
The largest cyclosporiasis outbreak in US history has exposed a dangerous gap in the way the nation’s foodborne disease surveillance works. With a food supply that moves fast and crosses borders, the system tracking its safety—through laboratory confirmations and traceback investigations—remains slow, complex, and vulnerable.
The artificial intelligence (AI) boom has ignited the demand for data centers. Goldman Sachs predicts a doubling of the power demand to run the data centers in just two years.
Generative AI tools such as ChatGPT, Gemini, and Preplexity require a significant amount of computing power to train large language models so they are able to answer user queries coming from the average person who is doing a search about basketball game statistics to investment bankers who are looking for nuggets of information that will help them invest in high return stocks.
As companies race to integrate artificial intelligence into the workplace, new research suggests workers benefit most when AI is paired with experience rather than treated as a replacement for it.
In most emergency departments, beds are a hot commodity. But some patients don’t actually need a bed for their treatment – and accurately identifying those people is a low-lift but effective way to increase efficiency without sacrificing care quality, finds a study recently published in the journal Management Science.
The researchers developed a simple decision tree, informed by mathematical and machine learning models, to help staff decide whether a patient truly needs a bed or can be routed to a “vertical processing pathway” – that is, an area where they can be treated sitting up. Many hospitals already have such an area but don’t necessarily have a systematic way to decide which patients are treated there.
OR/MS Today is the INFORMS member magazine that shares the latest research and best practices in operations research, analytics and the management sciences.
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Analytics magazine showcases articles and research reports based on big data, AI, machine learning, data analytics and other new-age technologies.
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