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Zeyad El Kelani on Muck Rack

Zeyad El Kelani

As seen in: HuffPost, MDPI, Taylor & Francis Online, BioRxiv
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Articles

Drug and Substance Abuse Point of Interest (POI) conflation and spatial attribute enrichment framework

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By Zeyad El Kelani, Mohamed Emish, Nahed T Zeini
| Taylor & Francis Online
ABSTRACT Point of Interest (POI) data is essential for accurate spatial analysis of pressing healthcare issues such as Drug and Substance Abuse (DSA). However, retrieving accurate healthcare POI information remains complicated. POI conflation integrates data from multiple sources to enhance spatial attribute quality and coverage.
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Is ChatGPT detrimental to innovation? A field experiment among university students

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By Sarah C Mansour, Zeyad El Kelani, Mazen Hassan, Engi Amin
| BioRxiv
Abstract ChatGPT represents a momentous technological breakthrough whose implications – along with other AI innovations – are yet to fully materialize. This paper is among the first attempts to experimentally test the effect of AI applications (in the form of ChatGPT) on three dependent variables usually assumed to be AI-collaterals: innovation, readiness to exert effort, and risk behaviour.
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A Mobile Health Application Using Geolocation for Behavioral Activity Tracking

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By Zeyad El Kelani, Maryam Hassani, Sean Young, Mohamed Emish
| MDPI
1. Introduction Geolocation tracking systems can unlock valuable insights into spatial health informatics by providing researchers and healthcare professionals with a rich source of health-related data [1]. The geographic distributions of geolocation data can be used to design more targeted and effective public health interventions, allocate resources to impoverished areas, and develop strategies for improving health outcomes for specific communities or populations [2].
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