James Lloyd, Robert Morse, Alasdair Taylor, David Phillips, Helen Higham, David Burckett-St Laurent, James Bowness
Artificial Intelligence: Innovation to Assist in the Identification of Sono-anatomy for Ultrasound-Guided Regional Anaesthesia
Advances in experimental medicine and biology
work examines influence reference dependence including value selection bias congruence effects diagnostic reasoning across two studies explored dependence initial problem structure influences ability solve simplified precursors traditional bayesian reasoning problems analyses evaluated accuracy types response errors function congruence problem presentation question interest amount information need computation individual differences numerical abilities across problem variations consistent strong evidence value selection bias incorrect responses almost always conformed values provided problem rather errors including related computation consistent unexpected error across conditions first experiment people often likely utilize superordinate value n part solution rather anticipated reference class values resulted weakened effect congruence relatively low accuracy even congruent conditions dominant response error superordinate value experiment 2 confirmed introduction new sample drew attention away provided reference class increasing reliance overall sample size superordinate preference error along benefit repeating ppv reference class within question demonstrated importance reference dependence based salience information within response prompt throughout higher numerical skills generally associated higher accuracy whether calculations required