Health care providers often are highly dependent on their health care IT supplier. That restricts the efficient exchange of data, and results in higher prices, reduced quality of care, and less innovation.’ What are some of the risks in the health care IT market? However, IT suppliers cannot foreclose markets. We also see that switching IT suppliers is very difficult and expensive. There is often a limited number of IT suppliers to choose from. That is why a well-functioning health care IT market is absolutely crucial for the quality, affordability, and accessibility of health care, now and in the future. Health care providers are highly dependent on IT systems for providing high-quality care to their patients. Martijn Snoep, Chairman of the Board of ACM, explains: ‘The exchange of data in the Dutch health care sector is lagging behind. ACM expects to finalize the guidelines in the fall. ![]() The Netherlands Authority for Consumers and Markets (ACM) has published the draft guidelines for public consultation thereof over the next few weeks. These are some of the recommendations in the draft version of the guidelines called ‘Well-functioning markets for health care IT’, which offers certainty to health care IT suppliers and health care providers in order to ensure that health care markets work better. To learn more about Clarify.ai, click here.No impediments to the exchange of data, no abuse of vendor lock-in, but, at the same time, giving room to collaborative procurement among health care providers, and the use of standards. Applying Clarify.ai to widefield data sets enables high signal-to-noise ratio results with high contrast while still maintaining the benefits of widefield microscopy.Ĭomputation is fast and can be applied at the experiment time, or later – it can even be applied to archived data for improvement of contrast. Widefield microscopy generally enables fast acquisition speeds and low system costs, and is readily applicable to imaging live specimens. No special hardware configuration is required for acquiring images suitable for Clarify.ai any fluorescence widefield images obtained from any detector can be used: including cell cultures, model organisms, tissue sections/slices, or other samples. Widefield image of Zebrafish vasculature, 20xĬlarify.ai can be used on any widefield 2D or 3D data set obtained from any microscope system, detector, or magnification, without the need for AI training or introduction of bias from complicated user-settings: it has been pre-trained to recognize and remove just the out-of-focus contributions from images and preserve the original details with one click. Widefield fluorescence image of brain slice, 40x It can also easily manage removal of heterogeneous scatter while preserving intensity linearity of the underlying data. This new AI-based module enables high-contrast results from any widefield fluorescent sample or acquisition magnification. ![]() Traditionally, deconvolution is used to reassign out-of-focus light, or additional hardware devices such as confocal pinholes used to reject this light.Ĭlarify.ai utilizes modern artificial intelligence deep learning technology to recognize out-of-focus light, and can automatically remove this component from widefield fluorescence images. ![]() In widefield fluorescence microscopy, image clarity can be impaired by out-of-focus signal emitted from above and below the focal plane. AI algorithm removes out of focus fluorescent signal
0 Comments
Leave a Reply. |