Advanced search
Publication Cover
Annals of Medicine Volume 51, 2019 - Issue 2
Submit an article Journal homepage
2,099
Views
34
CrossRef citations to date
0
Altmetric
Original Articles

Extensive phenotype data and machine learning in prediction of mortality in acute coronary syndrome – the MADDEC study

Jussi A. Hernesniemia Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland;b Department of Cardiology, Tays Heart Hospital, Tampere University Hospital, Tampere, FinlandCorrespondence[email protected]
View further author information
,
Shadi Mahdiania Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland;c VTT Technical Research Center of Finland, Tampere, FinlandView further author information
,
Juho A. Tynkkynena Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland;d Department of Radiology, Kanta-Häme Central Hospital, Hämeenlinna, FinlandView further author information
,
Leo-Pekka Lyytikäinena Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland;b Department of Cardiology, Tays Heart Hospital, Tampere University Hospital, Tampere, Finland;e Department of Clinical Chemistry, Fimlab Laboratories and Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, FinlandView further author information
,
Pashupati P. Mishrae Department of Clinical Chemistry, Fimlab Laboratories and Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, FinlandView further author information
,
Terho Lehtimäkia Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland;e Department of Clinical Chemistry, Fimlab Laboratories and Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, FinlandView further author information
,
Markku Eskolab Department of Cardiology, Tays Heart Hospital, Tampere University Hospital, Tampere, FinlandView further author information
,
Kjell Nikusa Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland;b Department of Cardiology, Tays Heart Hospital, Tampere University Hospital, Tampere, FinlandView further author information
,
Kari Antilac VTT Technical Research Center of Finland, Tampere, FinlandView further author information
&
Niku Oksalaa Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland;e Department of Clinical Chemistry, Fimlab Laboratories and Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland;f Vascular and Interventional Radiology Centre, Tampere University Hospital, Tampere, FinlandView further author information
 show all
Pages 156-163 | Received 12 Dec 2018, Accepted 11 Mar 2019, Published online: 27 Apr 2019

Citations (34)

Keep up to date with the latest research on this topic with citation updates for this article.

Subscribe to citation updates

Read on this site (2)

Ikram U Haq, Karanjot Chhatwal, Krishna Sanaka & Bo Xu. (2022) Artificial Intelligence in Cardiovascular Medicine: Current Insights and Future Prospects. Vascular Health and Risk Management 18, pages 517-528.
Read now
Markus Hautamäki, Leo-Pekka Lyytikäinen, Shadi Mahdiani, Markku Eskola, Terho Lehtimäki, Kjell Nikus, Kari Antila, Niku Oksala & Jussi Hernesniemi. (2020) The association between charlson comorbidity index and mortality in acute coronary syndrome – the MADDEC study. Scandinavian Cardiovascular Journal 54:3, pages 146-152.
Read now

Articles from other publishers (32)

Elias Parkkari, Ville Vanhala, Ronja Lindberg, Juho Tynkkynen & Jussi Hernesniemi. (2023) The incidence of atrial fibrillation, new oral anticoagulation, stroke, and significant bleeds in patients receiving a new dual-chamber pacemaker. IJC Heart & Vasculature 49, pages 101307.
Crossref
Onni Erkkilä, Jussi Hernesniemi & Juho Tynkkynen. (2023) The Association Between Digoxin Use and Long-Term Mortality After Acute Coronary Syndrome. The American Journal of Cardiology 204, pages 377-382.
Crossref
Roope Lahti, Jani Rankinen, Markku Eskola, Kjell Nikus & Jussi Hernesniemi. (2023) Intraventricular conduction delays as a predictor of mortality in acute coronary syndromes. European Heart Journal: Acute Cardiovascular Care 12:7, pages 430-436.
Crossref
Michele Ciccarelli, Francesco Giallauria, Albino Carrizzo, Valeria Visco, Angelo Silverio, Arturo Cesaro, Paolo Calabrò, Nicola De Luca, Costantino Mancusi, Daniele Masarone, Giuseppe Pacileo, Nidal Tourkmani, Carlo Vigorito & Carmine Vecchione. (2023) Artificial intelligence in cardiovascular prevention: new ways will open new doors. Journal of Cardiovascular Medicine 24:Supplement 2, pages e106-e115.
Crossref
Emmi Antikainen, Joonas Linnosmaa, Adil Umer, Niku Oksala, Markku Eskola, Mark van Gils, Jussi Hernesniemi & Moncef Gabbouj. (2023) Transformers for cardiac patient mortality risk prediction from heterogeneous electronic health records. Scientific Reports 13:1.
Crossref
Sayed Masoud Hosseini, Mitra Rahimi, Mohammad Reza Afrash, Pardis Ziaeefar, Parsa Yousefzadeh, Sanaz Pashapour, Peyman Erfan Talab Evini, Babak Mostafazadeh & Shahin Shadnia. (2023) Prediction of acute organophosphate poisoning severity using machine learning techniques. Toxicology 486, pages 153431.
Crossref
Xiaojie Chen, Han Chen, Shan Nan, Xiangtian Kong, Huilong Duan & Haiyan Zhu. (2023) Dealing With Missing, Imbalanced, and Sparse Features During the Development of a Prediction Model for Sudden Death Using Emergency Medicine Data: Machine Learning Approach. JMIR Medical Informatics 11, pages e38590.
Crossref
Syed Waseem Abbas Sherazi, Huilin Zheng, Saba Arif, Malik Muhammad Waqar, Gyeongtae Kim & Jong Yun Lee. (2023) A Deep-Learning Neural Network-Based Predictive System for the Occurrence of Major Adverse Cardiovascular Events (MACE) in Patients with Acute Myocardial Infarction. International Journal of Computer Theory and Engineering 15:3, pages 95-100.
Crossref
Matilda Hurskainen, Juho Tynkkynen, Markku Eskola & Jussi Hernesniemi. (2022) Incidence of stroke and mortality due to stroke after acute coronary syndrome. Journal of Stroke and Cerebrovascular Diseases 31:12, pages 106842.
Crossref
Roope Lahti, Jani Rankinen, Leo-Pekka Lyytikäinen, Markku Eskola, Kjell Nikus & Jussi Hernesniemi. (2022) High-risk ECG patterns in ST elevation myocardial infarction for mortality prediction. Journal of Electrocardiology 74, pages 13-19.
Crossref
Jaakko Lähteenmäki, Anna-Leena Vuorinen, Juha Pajula, Kari Harno, Mika Lehto, Mikko Niemi & Mark Van Gils. (2021) Integrating data from multiple Finnish biobanks and national health-care registers for retrospective studies: Practical experiences. Scandinavian Journal of Public Health 50:4, pages 482-489.
Crossref
Paul-Adrian Călburean, Paul Grebenișan, Ioana-Andreea Nistor, Krisztina Pal, Victor Vacariu, Reka-Katalin Drincal, Oana Țepes, Iulia Bârlea, Ioana Șuș, Cristina Somkereki, Valentin Șimon, Zoltán Demjén, István Adorján, Irina Pinitilie, Anca Teodora Dolcoș, Tiberiu Oltean, Marius Mărușteri, Elena Druica & László Hadadi. (2022) Prediction of 3-year all-cause and cardiovascular cause mortality in a prospective percutaneous coronary intervention registry: Machine learning model outperforms conventional clinical risk scores. Atherosclerosis 350, pages 33-40.
Crossref
Osung Kwon, Wonjun Na, Heejun Kang, Tae Joon Jun, Jihoon Kweon, Gyung-Min Park, YongHyun Cho, Cinyoung Hur, Jungwoo Chae, Do-Yoon Kang, Pil Hyung Lee, Jung-Min Ahn, Duk-Woo Park, Soo-Jin Kang, Seung-Whan Lee, Cheol Whan Lee, Seong-Wook Park, Seung-Jung Park, Dong Hyun Yang & Young-Hak Kim. (2022) Electronic Medical Record–Based Machine Learning Approach to Predict the Risk of 30-Day Adverse Cardiac Events After Invasive Coronary Treatment: Machine Learning Model Development and Validation. JMIR Medical Informatics 10:5, pages e26801.
Crossref
Sara Chopannejad, Farahnaz Sadoughi, Rafat Bagherzadeh & Sakineh Shekarchi. (2022) Predicting Major Adverse Cardiovascular Events in Acute Coronary Syndrome: A Scoping Review of Machine Learning Approaches. Applied Clinical Informatics 13:03, pages 720-740.
Crossref
Antti Jokiniitty, Markku Eskola, Tanja Saarela, Heini Huhtala & Saara Metso. (2022) Role of an automated screening tool for familial hypercholesterolemia in patients with premature coronary artery disease. Atherosclerosis Plus 48, pages 1-7.
Crossref
Abdallah Malkawi, Zaid Almarzooq, Mouaz H. Al-Mallah & Subhi J. Al’Aref. 2022. Artificial Intelligence in Cardiothoracic Imaging. Artificial Intelligence in Cardiothoracic Imaging 403 419 .
Amitava Banerjee, Suliang Chen, Ghazaleh Fatemifar, Mohamad Zeina, R. Thomas Lumbers, Johanna Mielke, Simrat Gill, Dipak Kotecha, Daniel F. Freitag, Spiros Denaxas & Harry Hemingway. (2021) Machine learning for subtype definition and risk prediction in heart failure, acute coronary syndromes and atrial fibrillation: systematic review of validity and clinical utility. BMC Medicine 19:1.
Crossref
Iqbal Madakkatel, Ang Zhou, Mark D. McDonnell & Elina Hyppönen. (2021) Combining machine learning and conventional statistical approaches for risk factor discovery in a large cohort study. Scientific Reports 11:1.
Crossref
Pengyue Wang, Maozu Guo, Yunsong Han, Lingling Zhao, Xiaoping Zhou & Dayu Zhang. (2021) Ensemble learning-based hierarchical retrieval of similar cases for site planning. Journal of Computational Design and Engineering 8:6, pages 1548-1561.
Crossref
Maribel González-Del-Hoyo & Xavier Rossello. (2021) Challenges and promises of machine learning-based risk prediction modelling in cardiovascular disease. European Heart Journal. Acute Cardiovascular Care 10:8, pages 866-868.
Crossref
Sebastian Weichwald, Alessandro Candreva, Rebekka Burkholz, Roland Klingenberg, Lorenz Räber, Dik Heg, Robert Manka, Baris Gencer, François Mach, David Nanchen, Nicolas Rodondi, Stephan Windecker, Reijo Laaksonen, Stanley L Hazen, Arnold von Eckardstein, Frank Ruschitzka, Thomas F Lüscher, Joachim M Buhmann & Christian M Matter. (2021) Improving 1-year mortality prediction in ACS patients using machine learning. European Heart Journal. Acute Cardiovascular Care 10:8, pages 855-865.
Crossref
Hong Wang, Quannan Zu, Jinglu Chen, Zhiren Yang & Mohammad Anis Ahmed. (2021) Application of Artificial Intelligence in Acute Coronary Syndrome: A Brief Literature Review. Advances in Therapy 38:10, pages 5078-5086.
Crossref
Markus Hautamäki, Leo-Pekka Lyytikäinen, Markku Eskola, Terho Lehtimäki, Kjell Nikus, Niku Oksala, Juho Tynkkynen & Jussi Hernesniemi. (2021) Prehospital Adenosine Diphosphate Receptor Blocker Use, Culprit Artery Flow, and Mortality in STEMI: The MADDEC Study. Clinical Drug Investigation 41:7, pages 605-613.
Crossref
Brett Snider, Edward A. McBean, John Yawney, S. Andrew Gadsden & Bhumi Patel. (2021) Identification of Variable Importance for Predictions of Mortality From COVID-19 Using AI Models for Ontario, Canada. Frontiers in Public Health 9.
Crossref
Lusha W. Liang, Michael A. Fifer, Kohei Hasegawa, Mathew S. Maurer, Muredach P. Reilly & Yuichi J. Shimada. (2021) Prediction of Genotype Positivity in Patients With Hypertrophic Cardiomyopathy Using Machine Learning. Circulation: Genomic and Precision Medicine 14:3.
Crossref
Jussi Tohka & Mark van Gils. (2021) Evaluation of machine learning algorithms for health and wellness applications: A tutorial. Computers in Biology and Medicine 132, pages 104324.
Crossref
Stephanie M. Kochav, Yoshihiko Raita, Michael A. Fifer, Hiroo Takayama, Jonathan Ginns, Mathew S. Maurer, Muredach P. Reilly, Kohei Hasegawa & Yuichi J. Shimada. (2021) Predicting the development of adverse cardiac events in patients with hypertrophic cardiomyopathy using machine learning. International Journal of Cardiology 327, pages 117-124.
Crossref
Xiaolin Diao, Yanni Huo, Zhanzheng Yan, Haibin Wang, Jing Yuan, Yuxin Wang, Jun Cai & Wei Zhao. (2021) An Application of Machine Learning to Etiological Diagnosis of Secondary Hypertension: Retrospective Study Using Electronic Medical Records. JMIR Medical Informatics 9:1, pages e19739.
Crossref
Davide Chicco & Giuseppe Jurman. (2021) Arterial Disease Computational Prediction and Health Record Feature Ranking Among Patients Diagnosed With Inflammatory Bowel Disease. IEEE Access 9, pages 78648-78657.
Crossref
Hema Sekhar Reddy Rajula, Giuseppe Verlato, Mirko Manchia, Nadia Antonucci & Vassilios Fanos. (2020) Comparison of Conventional Statistical Methods with Machine Learning in Medicine: Diagnosis, Drug Development, and Treatment. Medicina 56:9, pages 455.
Crossref
Zhongyu Wang, Hongbin Sun, Dong Zhao & Tiechao Jiang. (2020) Convolution Denoising Regularized Auto Encoder Stacked Method for Coronary Acute Syndrome in Internet of Medical Things Platform. IEEE Access 8, pages 57389-57399.
Crossref
Hao Mo, Hejiang Sun, Junjie Liu & Shen Wei. (2019) Developing window behavior models for residential buildings using XGBoost algorithm. Energy and Buildings 205, pages 109564.
Crossref

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Order Reprints Request Corporate Permissions

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

Request Academic Permissions

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.

Related research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.