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Prediction of Mortality Based on Facial Characteristics

Overview of attention for article published in Frontiers in Human Neuroscience, May 2016
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (95th percentile)
  • High Attention Score compared to outputs of the same age and source (94th percentile)

Mentioned by

blogs
3 blogs
twitter
39 X users
facebook
8 Facebook pages
wikipedia
1 Wikipedia page
googleplus
1 Google+ user

Citations

dimensions_citation
5 Dimensions

Readers on

mendeley
38 Mendeley
citeulike
2 CiteULike
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Title
Prediction of Mortality Based on Facial Characteristics
Published in
Frontiers in Human Neuroscience, May 2016
DOI 10.3389/fnhum.2016.00173
Pubmed ID
Authors

Arnaud Delorme, Alan Pierce, Leena Michel, Dean Radin

Abstract

Recent studies have shown that characteristics of the face contain a wealth of information about health, age and chronic clinical conditions. Such studies involve objective measurement of facial features correlated with historical health information. But some individuals also claim to be adept at gauging mortality based on a glance at a person's photograph. To test this claim, we invited 12 such individuals to see if they could determine if a person was alive or dead based solely on a brief examination of facial photographs. All photos used in the experiment were transformed into a uniform gray scale and then counterbalanced across eight categories: gender, age, gaze direction, glasses, head position, smile, hair color, and image resolution. Participants examined 404 photographs displayed on a computer monitor, one photo at a time, each shown for a maximum of 8 s. Half of the individuals in the photos were deceased, and half were alive at the time the experiment was conducted. Participants were asked to press a button if they thought the person in a photo was living or deceased. Overall mean accuracy on this task was 53.8%, where 50% was expected by chance (p < 0.004, two-tail). Statistically significant accuracy was independently obtained in 5 of the 12 participants. We also collected 32-channel electrophysiological recordings and observed a robust difference between images of deceased individuals correctly vs. incorrectly classified in the early event related potential (ERP) at 100 ms post-stimulus onset. Our results support claims of individuals who report that some as-yet unknown features of the face predict mortality. The results are also compatible with claims about clairvoyance warrants further investigation.

X Demographics

X Demographics

The data shown below were collected from the profiles of 39 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 38 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 32%
Student > Master 6 16%
Researcher 5 13%
Professor 5 13%
Student > Doctoral Student 3 8%
Other 4 11%
Unknown 3 8%
Readers by discipline Count As %
Psychology 13 34%
Medicine and Dentistry 7 18%
Agricultural and Biological Sciences 3 8%
Engineering 3 8%
Neuroscience 3 8%
Other 4 11%
Unknown 5 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 59. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 17 September 2022.
All research outputs
#738,507
of 25,711,518 outputs
Outputs from Frontiers in Human Neuroscience
#319
of 7,750 outputs
Outputs of similar age
#13,777
of 343,377 outputs
Outputs of similar age from Frontiers in Human Neuroscience
#11
of 189 outputs
Altmetric has tracked 25,711,518 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,750 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.0. This one has done particularly well, scoring higher than 95% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 343,377 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 95% of its contemporaries.
We're also able to compare this research output to 189 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 94% of its contemporaries.