Machine-Learning models able to predict risk of renal function decline 

By Shania Kennedy, contributing writer for 

Research has found that machine-learning (ML) models can use standard clinical data to predict renal function decline (RFD) with similar accuracy to that of traditional prediction methods. 


The evolution and expansion of AIOps in network management 

By Nitin Kumar, contributing writer for 

Expected to be worth more than $40 billion by 2026, AIOps solutions are paving the way for improved IT operations in digitally-driven organizations. A major factor driving this is that traditional operations management models are no longer good enough to deal with a world where distributed work has been normalized. Instead, by leveraging big data, machine learning, artificial intelligence (AI) and other advanced technologies, companies can bring greater automation to enterprise IT infrastructure and service management as well as gain complete visibility of the network infrastructure challenges they face. 


Multifamily only beginning to tap the property optimization potential of AI 

By Paul Bergeron, a contributing writer for 

Finally forced to embrace innovative solutions during the pandemic, multifamily made tremendous strides in terms of technology implementations over the past two years. Automations flourished as operators sought out contactless solutions. New operational efficiencies emerged as platforms were deployed to accommodate a remote workforce. 


How decision intelligence reduces cart abandonment and increases revenue  

By Ajay Khanna, contributing writer for 

Nearly 70 percent of online shopping carts today are abandoned, leaving a great deal of sales revenue on the table for retailers and e-commerce providers. To reduce cart abandonment, brands are relying on data that will inform them of shopper preferences and shape their marketing, sales and customer service experiences. Unfortunately, the sheer volume of commerce traveling through digital channels and the data it generates makes traditional analytics — like business intelligence dashboards — antiquated. Companies shouldn’t rely on legacy approaches and data structures that don’t take advantage of innovations such as automation, artificial intelligence, and machine learning. 


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