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Your search keyword '"Uffelmann, Jakob"' showing total 3 results
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3 results on '"Uffelmann, Jakob"'

2. Using an eHealth portal to transform PHC during the pandemic:How a national eHealth portal enabled a fast and inclusive response to the covid-19 pandemic

Author

Kayser, Lars, Banck, Sisse, Bang Jensen, Kristian, Uffelmann, Jakob, and Elbæk, Morten

Subjects
Faculty of Health and Medical Sciences, Health portal, Informatics, covid-19
Abstract

In Denmark, as in other countries, the COVID-19 pandemic has caused overload of the capacities of health systemsand an increase in deaths.The trusted Danish eHealth Portal has been instrumental in facilitating delivery of, and accessibility to, health services,including fast access to test results and documentation of vaccinations. It has also served as an information resourceenabling decision-making for citizens and health care professionals. The Portal has acted as a gatekeeper for access to Danish primary health care (PHC) services before and during the pandemic. Ultimately, it has become instrumental in moving toward digital health literacy in the population at large.The Portal and its support organization expanded swiftly during the pandemic to reinforce new digital solutions to ease access to services. Access to health data via the Portal has been expanded for PHC professionals to cover municipalities, allowing these to be part of the emergency response and to provide health care locally

Published
2022

3. Erroneous data: The Achilles' heel of AI and personalized medicine.

Author

Kristiansen TB, Kristensen K, Uffelmann J, and Brandslund I

Abstract

This paper reviews dilemmas and implications of erroneous data for clinical implementation of AI. It is well-known that if erroneous and biased data are used to train AI, there is a risk of systematic error. However, even perfectly trained AI applications can produce faulty outputs if fed with erroneous inputs. To counter such problems, we suggest 3 steps: (1) AI should focus on data of the highest quality, in essence paraclinical data and digital images, (2) patients should be granted simple access to the input data that feed the AI, and granted a right to request changes to erroneous data, and (3) automated high-throughput methods for error-correction should be implemented in domains with faulty data when possible. Also, we conclude that erroneous data is a reality even for highly reputable Danish data sources, and thus, legal framework for the correction of errors is universally needed., (Copyright © 2022 Kristiansen, Kristensen, Uffelmann and Brandslund.)

Published
2022
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