Why a Clinical Decision Support System is needed for Tinnitus?

Sarafidis, Michail; Manta, Ourania; Kouris, Ioannis; Schlee, Winfried; Kikidis, Dimitrios; Vellidou, Eleftheria; Koutsouris, Dimitrios

doi:10.1109/embc46164.2021.9630137

Cited by 6 publications

(4 citation statements)

References 24 publications

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“…In this regard, genetic tests and consultations are conducted for future parents, based on which final decisions are made. CDSS, which is currently being widely implemented in various fields of medicine, can undoubtedly provide significant assistance to physicians in the diagnosis and prognosis of hereditary pathologies [26].…”

Section: Discussionmentioning

confidence: 99%

Prevalence of thalassemia in the Vietnamese population and building a clinical decision support system for prenatal screening for thalassemia

et al. 2023

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The prevalence of thalassemia among the Vietnamese population was studied, and clinical decision support systems (CDSSs) for prenatal screening of thalassemia were created. A cross-sectional study was conducted on pregnant women and their husbands visiting from October 2020 to December 2021. A total of 10,112 medical records of first-time pregnant women and their husbands were collected. CDSS including two different types of systems for prenatal screening for thalassemia (expert system [ES] and four artificial intelligence [AI]-based CDSS) was built. 1,992 cases were used to train and test machine learning (ML) models while 1,555 cases were used for specialized ES evaluation. There were 10 key variables for AI-based CDSS for ML. The four most important features in thalassemia screening were identified. Accuracy of ES and AI-based CDSS was compared. The rate of patients with alpha thalassemia is 10.73% (1,085 patients), the rate of patients with beta-thalassemia is 2.24% (227 patients), and 0.29% (29 patients) of patients carry both alpha-thalassemia and beta-thalassemia gene mutations. ES showed an accuracy of 98.45%. Among AI-based CDSS developed, multilayer perceptron model was the most stable regardless of the training database (accuracy of 98.50% using all features and 97.00% using only the four most important features). AI-based CDSS showed satisfactory results. Further development of such systems is promising with a view to their introduction into clinical practice.

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Section: Discussionmentioning

confidence: 99%

Prevalence of thalassemia in the Vietnamese population and building a clinical decision support system for prenatal screening for thalassemia

et al. 2023

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“…The clinical decision support system (CDSS), which is currently being widely implemented in various fields of medicine, can undoubtedly provide significant assistance to physicians in the diagnosis and prognosis of hereditary pathologies. 26 …”

Section: Discussionmentioning

confidence: 99%

Prevalence of Thalassemia in the Vietnamese Population and Building a Clinical Decision Support System for Prenatal Screening for Thalassemia

Tran

Dang

Hoang

et al. 2023

Mediterr J Hematol Infect Dis

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Background and objectives. Investigating the prevalence of thalassemia in the Vietnamese population, building a clinical decision support system for prenatal screening for thalassemia. Methods. A cross-sectional study was conducted on pregnant women and their husbands visiting Vietnam National Hospital of Obstetrics and Gynecology from October 2020 to December 2021. Results. The clinical decision support system including 2 different types of systems for prenatal screening for thalassemia (expert system and 4 AI-based CDSS) was built. Accuracy of expert system and AI-based CDSS was compared. The rate of patients with Alpha thalassemia is 10.73%, the rate of patients with beta-thalassemia is 2.24%, and 0.29% of patients carry both alpha-thalassemia and beta-thalassemia gene mutations. The expert system showed an accuracy of 98.45%. Among the AI-based CDSS developed, the MLP model was the most stable regardless of the training database. Conclusions. When comparing the expert system with the AI-based CDSS, the accuracy of the expert system and AI-based models was found to be comparable. The developed expert system for prenatal thalassemia screening showed high accuracy. AI-based CDSS showed satisfactory results and can be applied in clinical practice.

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“…However these are fairly generic and in some cases recommendations are not definitive due to limited evidence. Decision support systems created from Big Data may guide effective treatment selection to aid clinicians (Sarafidis et al, 2021). Better service structures, support and tools for tinnitus care may encourage more clinicians to take up tinnitus practice.…”

Section: Create Better and More Accessible Servicesmentioning

confidence: 99%

Specialty grand challenge: Smarter solutions for tinnitus

Searchfield

2023

Front. Audiol. Otol.

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Why a Clinical Decision Support System is needed for Tinnitus?

Cited by 6 publications

References 24 publications

Prevalence of thalassemia in the Vietnamese population and building a clinical decision support system for prenatal screening for thalassemia

Prevalence of thalassemia in the Vietnamese population and building a clinical decision support system for prenatal screening for thalassemia

Prevalence of Thalassemia in the Vietnamese Population and Building a Clinical Decision Support System for Prenatal Screening for Thalassemia

Specialty grand challenge: Smarter solutions for tinnitus

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