A fresh look at ischaemic heart disease: from artificial intelligence to reappraisal of old drugs

Crea, Filippo

doi:10.1093/eurheartj/ehaa964

Cited by 3 publications

(2 citation statements)

References 14 publications

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“…Artificial intelligence (AI) is intelligence that is represented by a machine to show the behaviour of the object you want to imitate and all of this is used to facilitate human work in various fields (Aphinives & Aphinives, 2021;Cox, 2021;Crea, 2021;Goh et al, 2021;Karaca et al, 2021;Pepic et al, 2021;Rahimunnisa et al, 2021Scheetz et al, 2021Secinaro et al, 2021;Tamilselvi et al, 2021). Based on the need and importance of the role of AI, there is an urgency to carry out holistic research based on Bibliometric analysis related to the research trend of AI during Covif-19 pandemic.…”

Section: Introductionmentioning

confidence: 99%

Artificial Intelligence Research During COVID-19 Pandemic: Contributed to Future Education

Nurhasan¹,

Prahanı²,

Suprapto³

et al. 2022

INT J INSTRUCTION

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Besides being able to cause death, it turns out that the COVID-19 pandemic has caused problems in various sectors, including education, health, and Social Life. In addition, the COVID-19 pandemic also has an impact on the field of research, including the field of Artificial Intelligence (AI) which has become an interesting issue in the era of the Industrial Revolution 4.0. Based on Scopus data (search by article title, abstract, and keywords), it shows that there are 381,691 documents. Results of Bibliometric through VOSViewer found some parameters or interrelationships among variables to capture the trend and novelty of researching on AI During COVID-19 Pandemic, such as researching on AI During COVID-19 Pandemic and technology, detection, patient, diagnosis, performance, radiologist, feature, education, and image. Implication research in general evidence, (1) AI researchers have bright career opportunities in the present and the future. This is evident from the condition of the central role of AI in all lines of human life, (2) The trend of AI research is also classified as having a very large contribution to have entered various fields during the COVID-19 pandemic. (3) Including the prevention of COVID-19 transmission with AI, various tools and media have emerged in the medical world that provides many benefits. (4) AI needs more exploration in education field research. In the last five years, AI has made a major contribution advancing the field of education.

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Section: Introductionmentioning

confidence: 99%

Artificial Intelligence Research During COVID-19 Pandemic: Contributed to Future Education

Nurhasan¹,

Prahanı²,

Suprapto³

et al. 2022

INT J INSTRUCTION

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“…The application of artificial intelligence (AI) in medicine has achieved significant progress in medical researches (Crea, 2020;Xiang et al, 2020;Mervis, 2021). In most reported studies, medical AI systems perform excellently in both internal and external validations (Lin et al, 2018;Gurovich et al, 2019;Topol, 2019;Yamashita et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Application of Surgical Decision Model for Patients With Childhood Cataract: A Study Based on Real World Data

Chen

Xiang

et al. 2021

Front. Bioeng. Biotechnol.

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Reliable validated methods are necessary to verify the performance of diagnosis and therapy-assisted models in clinical practice. However, some validated results have research bias and may not reflect the results of real-world application. In addition, the conduct of clinical trials has executive risks for the indeterminate effectiveness of models and it is challenging to finish validated clinical trials of rare diseases. Real world data (RWD) can probably solve this problem. In our study, we collected RWD from 251 patients with a rare disease, childhood cataract (CC) and conducted a retrospective study to validate the CC surgical decision model. The consistency of the real surgical type and recommended surgical type was 94.16%. In the cataract extraction (CE) group, the model recommended the same surgical type for 84.48% of eyes, but the model advised conducting cataract extraction and primary intraocular lens implantation (CE + IOL) surgery in 15.52% of eyes, which was different from the real-world choices. In the CE + IOL group, the model recommended the same surgical type for 100% of eyes. The real-recommended matched rates were 94.22% in the eyes of bilateral patients and 90.38% in the eyes of unilateral patients. Our study is the first to apply RWD to complete a retrospective study evaluating a clinical model, and the results indicate the availability and feasibility of applying RWD in model validation and serve guidance for intelligent model evaluation for rare diseases.

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Machine Learning Identifies Clinical Parameters to Predict Mortality in Patients Undergoing Transcatheter Mitral Valve Repair

Zweck

Spieker

Horn

et al. 2021

JACC: Cardiovascular Interventions

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A fresh look at ischaemic heart disease: from artificial intelligence to reappraisal of old drugs

Cited by 3 publications

References 14 publications

Artificial Intelligence Research During COVID-19 Pandemic: Contributed to Future Education

Artificial Intelligence Research During COVID-19 Pandemic: Contributed to Future Education

Application of Surgical Decision Model for Patients With Childhood Cataract: A Study Based on Real World Data

Machine Learning Identifies Clinical Parameters to Predict Mortality in Patients Undergoing Transcatheter Mitral Valve Repair

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