Netflix was one of the earliest pioneers of online movie and TV streaming. Established in 1997, the company initially started as a mail-order DVD service with no late fees.
Delaware Health Information Network (DHIN, pronounced “DIN”) is a public instrumentality of the State of Delaware, established by legislation in 1997 as a public-private collaboration to resolve the need to share health data between care settings securely and to assist Public Health and other state authorities in the collection and analysis of health data needed during their work. Initially formed within a State agency, a board representing the various stakeholder groups decided DHIN’s course, with day-to-day operations supervised by a contracted Executive Director. From 2006, when DHIN first acquired the technology tools to “go live” with health data exchange, through 2010, the funding stream to support DHIN’s work was an almost equal blend of federal grants, a State capital appropriation over five years, and private funding sources. The intent was always that DHIN would develop to the point of financial sustainability without State financial support.
In 2010, DHIN’s enabling statute was amended to spin DHIN out from under the Health Care Commission as a semi-autonomous public instrumentality functioning as a not-for-profit business. The governor appointed a new board of directors, and Dr. Jan Lee was hired as the CEO. Under her leadership and vast work experience, DHIN has become the hub of a health information ecosystem in Delaware, and participation in one or more DHIN services is nearly universal across the Delaware healthcare community.
“DHIN’s mission is to make health data available when and where it is needed and to make the data useful through innovative solutions,” said Dr. Jan Lee, CEO of DHIN. The services at DHIN revolve around three key capabilities:
Neural networks, as their name implies, are computer algorithms modeled after networks of neurons in the human brain. Learn more about neural networks from Algorithmia.
Recurrent neural networks, also known as RNNs, are a class of neural networks that allow previous outputs to be used as inputs while having hidden states.
The purpose of this project is to build and evaluate Recurrent Neural Networks(RNNs) for sentence-level classification tasks. Let's understand about recurrent neural networks for multilabel text classification tasks.
Artificial neural networks (ANNs), usually simply called neural networks (NNs), are computing systems vaguely inspired by the biological neural networks that constitute animal brains.
Convolutional Neural Network: How is it different from the other networks? What’s so unique about CNNs and what does convolution really do? This is a math-free introduction to the wonders of CNNs.