Comput Methods Programs Biomed - The methodology of Dynamic Uncertain Causality Graph for intelligent diagnosis of vertigo.

Tópicos

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{ algorithm(1844) comput(1787) effici(935) }
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{ data(2317) use(1299) case(1017) }
{ age(1611) year(1155) adult(843) }
{ signal(2180) analysi(812) frequenc(800) }
{ cost(1906) reduc(1198) effect(832) }
{ group(2977) signific(1463) compar(1072) }
{ sampl(1606) size(1419) use(1276) }
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Resumo

Vertigo is a common complaint with many potential causes involving otology, neurology and general medicine, and it is fairly difficult to distinguish the vertiginous disorders from each other accurately even for experienced physicians. Based on comprehensive investigations to relevant characteristics of vertigo, we propose a diagnostic modeling and reasoning methodology using Dynamic Uncertain Causality Graph. The symptoms, signs, findings of examinations, medical histories, etiology and pathogenesis, and so on, are incorporated in the diagnostic model. A modularized modeling scheme is presented to reduce the difficulty in model construction, providing multiple perspectives and arbitrary granularity for disease causality representations. We resort to the "chaining" inference algorithm and weighted logic operation mechanism, which guarantee the exactness and efficiency of diagnostic reasoning under situations of incomplete and uncertain information. Moreover, the causal insights into underlying interactions among diseases and symptoms intuitively demonstrate the reasoning process in a graphical manner. These solutions make the conclusions and advices more explicable and convincing, further increasing the objectivity of clinical decision-making. Verification experiments and empirical evaluations are performed with clinical vertigo cases. The results reveal that, even with incomplete observations, this methodology achieves encouraging diagnostic accuracy and effectiveness. This study provides a promising assistance tool for physicians in diagnosis of vertigo.

Resumo Limpo

vertigo common complaint mani potenti caus involv otolog neurolog general medicin fair difficult distinguish vertigin disord accur even experienc physician base comprehens investig relev characterist vertigo propos diagnost model reason methodolog use dynam uncertain causal graph symptom sign find examin medic histori etiolog pathogenesi incorpor diagnost model modular model scheme present reduc difficulti model construct provid multipl perspect arbitrari granular diseas causal represent resort chain infer algorithm weight logic oper mechan guarante exact effici diagnost reason situat incomplet uncertain inform moreov causal insight under interact among diseas symptom intuit demonstr reason process graphic manner solut make conclus advic explic convinc increas object clinic decisionmak verif experi empir evalu perform clinic vertigo case result reveal even incomplet observ methodolog achiev encourag diagnost accuraci effect studi provid promis assist tool physician diagnosi vertigo

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