Ischemia and outcome prediction by cardiac CT based machine learning

Brandt, Verena; Emrich, Tilman; Schoepf, U. Joseph; Dargis, Danielle M.; Bayer, Richard R.; Cecco, Carlo N. De; Tesche, Christian

doi:10.1007/s10554-020-01929-y

Cited by 18 publications

(13 citation statements)

References 55 publications

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“…URL: https://medium.com/designkontur/простыми-словами-о-выборке-e6709423dfaa (дата обращения: 19.02.2022). 15 Колесников Ю. С. Методика проведения фокус-групп. Psyfactor.org.…”

Section: социология управленияunclassified

“…Был составлен список медицинских учреждений для проведения опроса и сформирована анкета, которая была выслана интервьюируемым заранее. Фокус-группы созавались на основе индикаторов, определяющих положение участников, и показателей, характеризующих их квалификацию, опыт работы, возраст и другие виды поведения 15 . При проведении опросов обеспечивалась гомогенность фокус-групп.…”

Section: социология управленияunclassified

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Areas for Artificial Intelligence Implementation in Kuzbass Healthcare: Sociological Aspects

Golovko

Kharlampenkov

2023

Bulletin of Kemerovo State University. Series: Political, Sociological and Economic Sciences

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The article analyzes the structure of morbidity in the region and identifies the main directions for artificial intelligence implementation in Russia. In order to identify the attitude of clinical physicians towards the artificial intelligence products, the authors performed a sociological survey. To develop the artificial intelligence in the Kemerovo Region it is necessary to use artificial intelligence products and build competence centers for implementing these products in regional healthcare. The main ways of development are strategic programs; creative teams within scientific and educational centers; introduction of automated workplaces for doctors. The authors’ proposals can improve the accuracy of diagnosis, simplify the treatment of patients with various diseases, and rise the healthcare of the Kemerovo region – Kuzbass to a new level.

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Section: социология управленияunclassified

Areas for Artificial Intelligence Implementation in Kuzbass Healthcare: Sociological Aspects

Golovko

Kharlampenkov

2023

Bulletin of Kemerovo State University. Series: Political, Sociological and Economic Sciences

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“…The application of artificial intelligence (AI) technology in cardiovascular imaging has become a research hotspot in recent years, as it may reduce treatment cost and help avoid unnecessary testing [1]. AI technology has been progressively applied for processing multiple modal images, such as auxiliary electrocardiograph diagnosis [2], cardiac computerized tomography (CT) detection [3], and radionuclide myocardial perfusion imaging [4]. In the diagnosis and treatment of heart diseases, AI techniques have been applied to electrocardiography, vectorcardiography, echocardiography, and electronic health records [5].…”

Section: Introductionmentioning

confidence: 99%

Artificial intelligence in echocardiography: detection, functional evaluation, and disease diagnosis

Zhou

Chang

et al. 2021

Cardiovasc Ultrasound

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Ultrasound is one of the most important examinations for clinical diagnosis of cardiovascular diseases. The speed of image movements driven by the frequency of the beating heart is faster than that of other organs. This particularity of echocardiography poses a challenge for sonographers to diagnose accurately. However, artificial intelligence for detection, functional evaluation, and disease diagnosis has gradually become an alternative for accurate diagnosis and treatment using echocardiography. This work discusses the current application of artificial intelligence in echocardiography technology, its limitations, and future development directions.

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“…Coronary CT angiography (cCTA) is a well-established modality for the assessment of coronary artery disease (CAD) and non-invasive plaque quanti cation [1][2][3]. Recent studies have demonstrated the predictive value of coronary plaque measures (i.e.…”

Section: Introductionmentioning

confidence: 99%

Prognostic Utility of Coronary CT Angiography-derived Plaque Information on Long-Term Outcome in Patients With and Without Diabetes mellitus

Tesche¹,

Baquet²,

Bauer³

et al. 2021

Preprint

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PurposeTo investigate the long-term prognostic value of coronary CT angiography (cCTA)-derived plaque information on major adverse cardiac events (MACE) in patients with and without diabetes mellitus. Methods64 patients with diabetes (63.3±10.1 years, 66% male) and suspected coronary artery disease (CAD) who underwent cCTA were matched with 297 patients without diabetes according to age, sex, cardiovascular risk factors, statin and antithrombotic therapy. Major adverse cardiac events (MACE) were recorded. cCTA-derived risk scores and plaque measures were assessed. The discriminatory power to identify MACE was evaluated using multivariable regression analysis and concordance indices (CIs).ResultsAfter a median follow-up of 5.4 years, MACE occurred in 31 patients (8.6%). In patients with diabetes, cCTA risk scores and plaque measures were significantly higher compared to non-diabetic patients (all p<0.05). The following plaque measures were predictors of MACE using multivariable Cox regression analysis (hazard ratio [HR]) in patients with diabetes: segment stenosis score (HR 1.20, p<0.001), low-attenuation plaque (HR 3.47, p=0.05), and in non-diabetic patients: segment stenosis score (HR 1.92, p<0.001), Agatston score (HR 1.0009, p=0.04), and low-attenuation plaque (HR 4.15, p=0.04). A multivariable model showed significantly improved C-index of 0.96 (95% CI 0.94-0.0.97) for MACE prediction, when compared to single measures alone.ConclusionDiabetes is associated with a significantly higher extent of CAD and plaque features, which have independent predictive values for MACE. cCTA-derived plaque information portends improved risk stratification of patients with diabetes beyond assessment of obstructive stenosis on cCTA alone.

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Ischemia and outcome prediction by cardiac CT based machine learning

Cited by 18 publications

References 55 publications

Areas for Artificial Intelligence Implementation in Kuzbass Healthcare: Sociological Aspects

Areas for Artificial Intelligence Implementation in Kuzbass Healthcare: Sociological Aspects

Artificial intelligence in echocardiography: detection, functional evaluation, and disease diagnosis

Prognostic Utility of Coronary CT Angiography-derived Plaque Information on Long-Term Outcome in Patients With and Without Diabetes mellitus

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