Publications by authors named "Z Kaufman"
The xCures platform aggregates, organizes, structures, and normalizes clinical EMR data across care sites, utilizing advanced technologies for near real-time access. The platform generates data in a format to support clinical care, accelerate research, and promote artificial intelligence/ machine learning algorithm development, highlighted by a clinical decision support algorithm for precision oncology.
View Article and Find Full Text PDFMy Model is Unfair, Do People Even Care? Visual Design Affects Trust and Perceived Bias in Machine Learning.
IEEE Trans Vis Comput Graph
January 2024
Machine learning technology has become ubiquitous, but, unfortunately, often exhibits bias. As a consequence, disparate stakeholders need to interact with and make informed decisions about using machine learning models in everyday systems. Visualization technology can support stakeholders in understanding and evaluating trade-offs between, for example, accuracy and fairness of models.
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- - The study examines the impact of the COVID-19 pandemic on excess mortality across 20 countries during 2020, focusing on overall mortality as well as differences based on sex and age.
- - By analyzing data from national vital statistics for the years 2015 to 2020, the researchers calculated excess mortality for 2020 by comparing observed weekly deaths to expected numbers based on historical trends.
- - Results showed significant excess mortality in several countries, particularly among older adults and generally higher in males, underscoring the need for ongoing monitoring to understand the pandemic's varied effects.
Background: Two SARS-CoV-2 waves in Israel ended while a substantial number of individuals remained unvaccinated or partially vaccinated. The indirect protective effect of the first BNT162b2 vaccination campaign in Israel was evaluated between 22 December 2020 and 18 May 2021.
Methods: The daily percentage of new polymerase chain reaction (PCR)-confirmed SARS-CoV-2 cases among unvaccinated individuals was analyzed for trends.
BackgroundThe COVID-19 pandemic presented new challenges for the existing respiratory surveillance systems, and adaptations were implemented. Systematic assessment of the syndromic and sentinel surveillance platforms during the pandemic is essential for understanding the value of each platform in the context of an emerging pathogen with rapid global spread.AimWe aimed to evaluate systematically the performance of various respiratory syndromic surveillance platforms and the sentinel surveillance system in Israel from 1 January to 31 December 2020.
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