Sinan Paslı, Abdul Samet Şahin, Muhammet Fatih Beşer, Hazal Topçuoğlu, Metin Yadigaroğlu, Melih İmamoğlu
Assessing the precision of artificial intelligence in ED triage decisions: Insights from a study with ChatGPT
The American journal of emergency medicine
analyze possibilities using russian version thought language communication scale tlc early recognition thought disorders patients clinical highrisk schizophrenia main group study included 30 adolescent male patients 19222 years hospitalized first depressive episode icd10 f321 f322 f3228 f328 demonstrated attenuated schizophrenic symptoms ass structure depression made possible attribute patients group clinical highrisk schizophrenia control group consisted 27 mentally healthy adolescent males 20023 years groups severity thought impairment assessed using tlc scale psychopathological psychometric statistical methods used median values severity thought impairment using tlc scale 20 points 1975 26 main group 105 points 925 13 control group high degree statistical significance p0001 significant differences p0001 found following parameters incoherence 2 1 3 vs 1 0 1 tangentiality 2 2 2 vs 1 0 2 derailment 2 125 2 vs 1 05 2 illogical thinking 2 2 275 vs 0 0 1 loss goal 1 0 2 vs 0 0 0 blocking 1 0 1 vs 0 0 0 accordingly specific related depression disorders thinking patients clinical group indicates signs disorganization thinking suggests beginning endogenous process schizophrenic pole found results show tlc scale used detect early cognitive disorders patients risk schizophrenia