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Daniel Dahm
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Daniel Dahm

Digital Content Manager

AS SEEN ON
WKMG News 6

Preston's Summary

Daniel Dahm is a Digital Content Manager at News6WKMG. With a strong focus on counterterrorism, law enforcement technology, and the intersection of police work and deep learning, Daniel brings a keen nose for news to his role. He has been featured in WJXT, WKMG News 6, WPLG Local 10 News, and Wiley.

Preston is the artificial intelligence that powers the Intelligent Relations PR platform. Meet Preston

Geo Focus

Orlando, United States (Local)

Coverage Attributes:

Beta
Informative: 63 %
Evolving Stories: 10 %
Events: 9 %
Breaking News: 8 %
Government Announcement: 1 %

Themes Covered:

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Most Recent Topics:

  • Counterterrorism
  • Law Enforcement Technology
  • Police
  • Deep Learning

Pitching Insights

Daniel Dahm's coverage focuses heavily on local breaking news and evolving stories, with a predominant emphasis on crime-related incidents such as traffic accidents, missing persons cases, and tragedies. If you are reaching out to Daniel, focus your pitches on providing information related to ongoing or developing local incidents in the Orlando area.

Consider offering timely updates or expert insights concerning evolving crime-related events like traffic accidents or missing person reports occurring within Central Florida. Additionally, if there are any local entertainment events tied to tragedy that he may cover occasionally, those could be worth considering for outreach.

This information evolves through artificial intelligence and human feedback. Improve this profile .

Articles

Wiley

Deep Learning HASTE for Upper Abdominal MRI: Improved Image Quality, Speed, and Energy Efficiency in a Prospective Study

Deep Learning HASTE for Upper Abdominal MRI: Improved Image Quality, Speed, and Energy Efficiency in a Prospective Study

By: Paul Konrad, Scherwin Mahmoudi, Philipp Reschke, Simon Bernatz, Renate M. Hammerstingl, Christophe Weber, Dominik Nickel, Simon S. Martin, Elena Höhne, Katrin Eichler, Stefan Zeuzem, Saber Al-Saleh, Vitali Koch, Tatjana Gruber-Rouh, Ralph Strecker, Jennifer Got, Ta, Daniel Dahm, Armin Wiegering, Tommaso D'Angelo, Thomas J. Vogl, Ralph Sinkus, Leon D. Gruenewald, Christian Booz, Ahmed Ait Bachir, Sebastian M. Haberkorn

The DL HASTE sequence enhanced image quality and diagnostic confidence while minimizing artifacts, time, and energy costs, enabling a more accurate detection of pathologies than the conventional T2-w...

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