Predicting cardiovascular health trajectories in time-series electronic health records with LSTM models

Medicine & Life Sciences

• Long-Term Memory 100%
• Electronic Health Records 88%
• Short-Term Memory 81%
• Health 42%
• Health Status 33%
• Cardiovascular Diseases 20%
• LDL Lipoproteins 19%
• Population Health Management 15%
• Smoking 13%
• Body Mass Index 13%
• Blood Pressure 12%
• Ambulatory Care Facilities 9%
• Health Care Costs 8%
• Hemoglobins 7%
• Cause of Death 7%
• Datasets 7%
• Quality of Life 6%
• Guidelines 6%

Social Sciences

• time series 91%
• electronics 60%
• health 39%
• cardiovascular disease 20%
• blood pressure 13%
• smoking 10%
• recipient 9%
• outpatient clinic 7%
• cause of death 6%
• health promotion 5%