AI & RoboticsNews

HealthTensor raises $5 million for AI that augments and corrects medical records

HealthTensor, a Los Angeles, California-based startup creating software to augment medical decision-making, today announced it has raised $5 million. The company says the funds will be used to scale up operations and acquire new customers. The global market for big data analytics in health care was valued at $16.87 billion in 2017 and is projected to reach $67.82 billion by 2025, according to a…
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AI & RoboticsNews

AI in health care creates unique data challenges

This article is part of a VB special issue. Read the full series: AI and the future of health care The health care industry produces an enormous amount of data. An IDC study estimates the volume of health data created annually, which hit over 2,000 exabytes in 2020, will continue to grow at a 48% rate year over year. Accelerated by the passage of the U.S. Patient Protection and Affordable Care…
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AI & RoboticsNews

Avaya expands its alliance with Google for AI for contact centers

Avaya has extended the capabilities of its contact center platforms to include an enhanced version of Google Cloud Dialogflow CX that can be employed to create virtual agents infused with AI capabilities that can verbally interact with customers. Residing on the Contact Center AI (CCAI) cloud service provided by Google, the conversational AI capabilities being provided by Avaya are enabled using…
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AI & RoboticsNews

AI needs an open labeling platform

These days it’s hard to find a public company that isn’t talking up how artificial intelligence is transforming its business. From the obvious (Tesla using AI to improve auto-pilot performance) to the less obvious (Levis using AI to drive better product decisions)…
AI & RoboticsNews

AI Weekly: Announcing our ‘AI and the future of health care’ special issue

Artificial intelligence and health care both deal heavily with issues of complexity, efficacy, and societal impact. All of that is multiplied when the two intersect. As health care providers and vendors work to use AI and data to improve patient care, health outcomes, medical research, and more, they face what are now standard AI challenges. Data is difficult and messy. Machine learning models…
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