nlp logix
NLP Logix Joins Beeline Partner Ecosystem
NLP Logix, an artificial intelligence and machine learning solutions company, today announced it's partnership and inclusion into the Beeline ecosystem. Beeline customers will be able to leverage NLP Logix's task automation solutions to drive even greater efficiencies. Beeline is the leading technology solution provider for managing the global extended workforce. "NLP Logix's AI tools can eliminate repetitive tasks, allowing the contingent workforce to offer even more value." "Beeline's mission is to optimize the contingent workforce in every way and partnering with NLP Logix will add another layer to this optimization," said Doug Leeby, Beeline CEO.
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Data Dimensions Teams with NLP Logix to Add b AI /b to Solutions
The combination of combined with NLP's technology, and Data Dimensions' subject matter experts on process flow, and large amounts of training data to apply algorithms to train the computers will enable the companies to deliver AI solutions to clients across many industries, added Marsh, co-founder … Read more: Data Dimensions Teams with NLP Logix to Add AI to Solutions
NLP Logix Receives Recognition for Developing a Machine Learning Model that Helps Identify and Classify Cancer Cells
Computer-aided algorithms are helping pathologists more efficiently and accurately identify cancer stages to deliver targeted treatment. Jacksonville-based advanced data analytics and machine learning solutions company NLP Logix continues to lead the way in the emerging field of computer vision, receiving recognition as the only United States team to deliver a top-winning solution in an international competition to develop a machine learning model that can help identify and treat cancer cells by stage level. NLP Logix recently earned a top-three finish position in the HER2 Challenge, an academic research competition sponsored by the University of Warwick's Department of Computer Science. More than 100 data science teams worldwide competed in the challenge which asked applicants to create algorithms to automate "scoring" of large-file images of stained slides of breast cancer cells based on the aggressiveness of the cancer. The method is used to detect the presence of the gene for HER2, a transmembrane growth factor receptor which is found in about 20 percent of cases of invasive cancer.