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Detection bias occurs when a phenomenon is more likely to be observed for a particular set of study subjects. For instance, the syndemic involving obesity and diabetes may mean doctors are more likely to look for diabetes in obese patients than in thinner patients, leading to an inflation in diabetes among obese patients because of skewed detection efforts.
Observer bias is commonly only identified in the observers, however, there also exists a bias for those being studied. Named after a series of experiments conducted by Elton Mayo between 1924 and 1932, at the Western Electric factory in Hawthorne, Chicago, the Hawthorne effect symbolises where the participants in a study change their behaviour ...
Lead time bias happens when survival time appears longer because diagnosis was done earlier (for instance, by screening), irrespective of whether the patient lived longer. Lead time is the duration of time between the detection of a disease (by screening or based on new experimental criteria) and its usual clinical presentation and diagnosis ...
Agent detection bias, the inclination to presume the purposeful intervention of a sentient or intelligent agent. Automation bias , the tendency to depend excessively on automated systems which can lead to erroneous automated information overriding correct decisions.
In 2016, the World Economic Forum claimed we are experiencing the fourth wave of the Industrial Revolution: automation using cyber-physical systems. Key elements of this wave include machine ...
Detection theory or signal detection theory is a means to measure the ability to differentiate between information-bearing patterns (called stimulus in living organisms, signal in machines) and random patterns that distract from the information (called noise, consisting of background stimuli and random activity of the detection machine and of the nervous system of the operator).
An asymmetric funnel indicates a relationship between treatment effect estimate and study precision. This suggests the possibility of either publication bias or a systematic difference between studies of higher and lower precision (typically ‘small study effects’). Asymmetry can also arise from use of an inappropriate effect measure.
Imagine an algorithm that reviews thousands of financial transactions every second and flags the fraudulent ones. This is something that has become possible thanks to advances in artificial ...