This paper is in the following e-collection/theme issue:

Clinical Information and Decision Making (1407) Decision Support for Health Professionals (1185) Electronic Health Records (1053) Machine Learning (1465) Hypertension Prevention and Treatment (224)

Published on in Vol 20, No 1 (2018): January

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/9268, first published .
Prediction of Incident Hypertension Within the Next Year: Prospective Study Using Statewide Electronic Health Records and Machine Learning

Prediction of Incident Hypertension Within the Next Year: Prospective Study Using Statewide Electronic Health Records and Machine Learning

Prediction of Incident Hypertension Within the Next Year: Prospective Study Using Statewide Electronic Health Records and Machine Learning

Authors of this article:

Chengyin Ye1, 2 Author Orcid Image ;   Tianyun Fu3 Author Orcid Image ;   Shiying Hao4, 5 Author Orcid Image ;   Yan Zhang6 Author Orcid Image ;   Oliver Wang3 Author Orcid Image ;   Bo Jin3 Author Orcid Image ;   Minjie Xia3 Author Orcid Image ;   Modi Liu3 Author Orcid Image ;   Xin Zhou7 Author Orcid Image ;   Qian Wu8 Author Orcid Image ;   Yanting Guo2, 9 Author Orcid Image ;   Chunqing Zhu3 Author Orcid Image ;   Yu-Ming Li7 Author Orcid Image ;   Devore S Culver10 Author Orcid Image ;   Shaun T Alfreds10 Author Orcid Image ;   Frank Stearns3 Author Orcid Image ;   Karl G Sylvester2 Author Orcid Image ;   Eric Widen3 Author Orcid Image ;   Doff McElhinney4, 5 Author Orcid Image ;   Xuefeng Ling2, 5, 11 Author Orcid Image
Article Authors Cited by (148) Tweetations (13) Metrics

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  107. Almansouri N, Awe M, Rajavelu S, Jahnavi K, Shastry R, Hasan A, Hasan H, Lakkimsetti M, AlAbbasi R, Gutiérrez B, Haider A. Early Diagnosis of Cardiovascular Diseases in the Era of Artificial Intelligence: An In-Depth Review. Cureus 2024 View
  108. Schjerven F, Ingeström E, Steinsland I, Lindseth F. Development of risk models of incident hypertension using machine learning on the HUNT study data. Scientific Reports 2024;14(1) View
  109. Chen J, Yuan D, Dong R, Cai J, Ai Z, Zhou S. Artificial intelligence significantly facilitates development in the mental health of college students: a bibliometric analysis. Frontiers in Psychology 2024;15 View
  110. Yang W, Yi D, Zhou X, Leng Y. Translational analysis of data science and causal learning in real-world clinical evaluation of traditional Chinese medicine. Science of Traditional Chinese Medicine 2024;2(1):57 View
  111. Park H, Jung S, Han M, Jang Y, Moon Y, Kim T, Shin S, Hwang H. Lowering Barriers to Health Risk Assessments in Promoting Personalized Health Management. Journal of Personalized Medicine 2024;14(3):316 View
  112. Wei C, Wang J, Yu P, Li A, Xiong Z, Yuan Z, Yu L, Luo J. Comparison of different machine learning classification models for predicting deep vein thrombosis in lower extremity fractures. Scientific Reports 2024;14(1) View
  113. Layton A. AI, Machine Learning, and ChatGPT in Hypertension. Hypertension 2024;81(4):709 View
  114. Zheng H, Sherazi S, Lee J. A cost-sensitive deep neural network-based prediction model for the mortality in acute myocardial infarction patients with hypertension on imbalanced data. Frontiers in Cardiovascular Medicine 2024;11 View
  115. Armoundas A, Narayan S, Arnett D, Spector-Bagdady K, Bennett D, Celi L, Friedman P, Gollob M, Hall J, Kwitek A, Lett E, Menon B, Sheehan K, Al-Zaiti S. Use of Artificial Intelligence in Improving Outcomes in Heart Disease: A Scientific Statement From the American Heart Association. Circulation 2024;149(14) View
  116. Cho J, Park J. Application of artificial intelligence in hypertension. Clinical Hypertension 2024;30(1) View
  117. Kapoor S, Cantrell E, Peng K, Pham T, Bail C, Gundersen O, Hofman J, Hullman J, Lones M, Malik M, Nanayakkara P, Poldrack R, Raji I, Roberts M, Salganik M, Serra-Garcia M, Stewart B, Vandewiele G, Narayanan A. REFORMS: Consensus-based Recommendations for Machine-learning-based Science. Science Advances 2024;10(18) View
  118. Kulvinder Singh , Dhawan S, Mehla D. Performance Evaluation of Machine Learning Models for Multiple Chronic Disease Diagnosis Using Symptom Data. Automatic Control and Computer Sciences 2024;58(2):195 View
  119. Kaur S, Gulati H, Baldi A. Digitalization of hypertension management: a paradigm shift. Naunyn-Schmiedeberg's Archives of Pharmacology 2024;397(11):8477 View
  120. Seedat N, Imrie F, Schaar M. Navigating Data-Centric Artificial Intelligence With DC-Check: Advances, Challenges, and Opportunities. IEEE Transactions on Artificial Intelligence 2024;5(6):2589 View
  121. Norrman A, Hasselström J, Ljunggren G, Wachtler C, Eriksson J, Kahan T, Wändell P, Gudjonsdottir H, Lindblom S, Ruge T, Rosenblad A, Brynedal B, Carlsson A. Predicting new cases of hypertension in Swedish primary care with a machine learning tool. Preventive Medicine Reports 2024;44:102806 View
  122. Juyal A, Bisht S, Singh M. Smart solutions in hypertension diagnosis and management: a deep dive into artificial intelligence and modern wearables for blood pressure monitoring. Blood Pressure Monitoring 2024;29(5):260 View
  123. 钟 玮. Risk Prediction of Hematoma Expansion in Hemorrhagic Stroke Patients Based on XGBoost Algorithm. Modeling and Simulation 2024;13(04):4271 View
  124. Jahangir Z, Muddassir Qureshi S, Abdul Rehman Y, Ur Rehman Shah S, Ahmed Qureshi H, Ahmad A. Revolutionizing AI-driven Hypertension Care: A Review of Current Trends and Future Directions. Journal of Science & Technology 2024;5(4):99 View
  125. Wang T, Tan J, Wang T, Xiang S, Zhang Y, Jian C, Jian J, Zhao W. A Real-World Study on the Short-Term Efficacy of Amlodipine in Treating Hypertension Among Inpatients. Pragmatic and Observational Research 2024;Volume 15:121 View
  126. Chen S, Yu J, Chamouni S, Wang Y, Li Y. Integrating machine learning and artificial intelligence in life-course epidemiology: pathways to innovative public health solutions. BMC Medicine 2024;22(1) View
  127. Guerreiro J, Garriga R, Lozano Bagén T, Sharma B, Karnik N, Matić A. Transatlantic transferability and replicability of machine-learning algorithms to predict mental health crises. npj Digital Medicine 2024;7(1) View
  128. Kario K, Williams B, Tomitani N, McManus R, Schutte A, Avolio A, Shimbo D, Wang J, Khan N, Picone D, Tan I, Charlton P, Satoh M, Mmopi K, Lopez-Lopez J, Bothe T, Bianchini E, Bhandari B, Lopez-Rivera J, Charchar F, Tomaszewski M, Stergiou G. Innovations in blood pressure measurement and reporting technology: International Society of Hypertension position paper endorsed by the World Hypertension League, European Society of Hypertension, Asian Pacific Society of Hypertension, and Latin American Society of Hypertension. Journal of Hypertension 2024;42(11):1874 View
  129. Li C, Mowery D, Ma X, Yang R, Vurgun U, Hwang S, Donnelly H, Bandhey H, Senathirajah Y, Visweswaran S, Sadhu E, Akhtar Z, Getzen E, Freda P, Long Q, Becich M. Realizing the potential of social determinants data in EHR systems: A scoping review of approaches for screening, linkage, extraction, analysis, and interventions. Journal of Clinical and Translational Science 2024;8(1) View
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  131. Singh C, Sodhi K. Targeting bioinformatics tools to study the dissemination and spread of antibiotic resistant genes in the environment and clinical settings. Critical Reviews in Microbiology 2024:1 View

Books/Policy Documents

  1. Cho P, Singh K, Dunn J. Artificial Intelligence in Medicine. View
  2. Srivani M, Mala T, Murugappan A. Handbook of Research on Emerging Trends and Applications of Machine Learning. View
  3. Chaturvedi A, Srivastava S, Rai A, Cheema A, Chelimela D, Aravindakshan R. Evolving Technologies for Computing, Communication and Smart World. View
  4. Koshimizu H, Okuno Y. Artificial Intelligence in Medicine. View
  5. Koshimizu H, Okuno Y. Artificial Intelligence in Medicine. View
  6. S. Allen K, Gilliam N, Kharrazi H, McPheeters M, Dixon B. Health Information Exchange. View
  7. El Sherbini A, Glicksberg B, Krittanawong C. Artificial Intelligence in Clinical Practice. View
  8. Kumar R, Adatia A, Wander G, Sahani A. Proceedings of International Conference on Frontiers in Computing and Systems. View
  9. Deorankar P, Vaidya V, Munot N, Jain K, Patil A. Biosystems, Biomedical & Drug Delivery Systems. View
  10. Ongwere T, Rutuja N, Nguyen T. Intelligent Computing. View
  11. Lee S, Leung F, Wong W, Chang C, Liu T, Tse G. Internet of Things and Machine Learning for Type I and Type II Diabetes. View