Create sustainable asset management with real-time data and predictive analytics
By Bryan Friehauf, contributing writer for Solutionsreview.com
The asset management challenges facing companies have shifted dramatically over the past few years. Global economic uncertainty, the ongoing supply chain crisis, and a looming recession have only added pressure on industry leaders as they navigate the changing landscape. There is also a sense of urgency to bring a sustainability lens to their work as the Biden Administration continues to push for net zero emissions by 2050. The recent Inflation Reduction Act (IRA) only advances the administration’s war on climate change, sending industry leaders a clear message—sustainability and renewable energy need to be top of mind not in the distant future but in the present.
Machine-learning model provides predictions on physician turnover
By Mark Melchionna, contributing writer for Healthitanalytics.com
A recent study by Yale University researchers detailed the creation of a machine-learning model that can assist researchers in determining physician turnover, enabling healthcare organizations to intervene and increase retention.
How AI and ML are transforming the supply chain
By Amit Prasad, contributing writer for Supplychainbrain.com
With recent disruptions such as the pandemic and hurricanes accounting for billions of dollars in damages, the need for creating a more resilient supply chain network with greater visibility and connectivity has increased. Artificial intelligence (AI), machine learning (ML) and data analytics have proven to be innovative solutions to these challenges and have the potential to transform supply chains.
Efficient technique improves machine-learning models’ reliability
By Adam Zewe, contributing writer for News.mit.edu
Powerful machine-learning models are being used to help people tackle tough problems such as identifying disease in medical images or detecting road obstacles for autonomous vehicles. But machine-learning models can make mistakes, so in high-stakes settings it’s critical that humans know when to trust a model’s predictions.
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