Published on in Vol 3, No 1 (2015): Jan-Mar
Journals
- Perner A, Gordon A, Angus D, Lamontagne F, Machado F, Russell J, Timsit J, Marshall J, Myburgh J, Shankar-Hari M, Singer M. The intensive care medicine research agenda on septic shock. Intensive Care Medicine 2017;43(9):1294 View
- Kim M, Tagkopoulos I. Data integration and predictive modeling methods for multi-omics datasets. Molecular Omics 2018;14(1):8 View
- Horng S, Sontag D, Halpern Y, Jernite Y, Shapiro N, Nathanson L, Groza T. Creating an automated trigger for sepsis clinical decision support at emergency department triage using machine learning. PLOS ONE 2017;12(4):e0174708 View
- Taneja I, Reddy B, Damhorst G, Dave Zhao S, Hassan U, Price Z, Jensen T, Ghonge T, Patel M, Wachspress S, Winter J, Rappleye M, Smith G, Healey R, Ajmal M, Khan M, Patel J, Rawal H, Sarwar R, Soni S, Anwaruddin S, Davis B, Kumar J, White K, Bashir R, Zhu R. Combining Biomarkers with EMR Data to Identify Patients in Different Phases of Sepsis. Scientific Reports 2017;7(1) View
- Horiguchi H, Loftus T, Hawkins R, Raymond S, Stortz J, Hollen M, Weiss B, Miller E, Bihorac A, Larson S, Mohr A, Brakenridge S, Tsujimoto H, Ueno H, Moore F, Moldawer L, Efron P. Innate Immunity in the Persistent Inflammation, Immunosuppression, and Catabolism Syndrome and Its Implications for Therapy. Frontiers in Immunology 2018;9 View
- Ocampo-Quintero N, Vidal-Cortés P, del Río Carbajo L, Fdez-Riverola F, Reboiro-Jato M, Glez-Peña D. Enhancing sepsis management through machine learning techniques: A review. Medicina Intensiva 2022;46(3):140 View
- Nibbelink C, Young J, Carrington J, Brewer B. Informatics Solutions for Application of Decision-Making Skills. Critical Care Nursing Clinics of North America 2018;30(2):237 View
- KENNEDY D, P. PHILBIN S. The imperative need to develop guidelines to manage human versus machine intelligence. Frontiers of Engineering Management 2018;0(0):0 View
- Belard A, Buchman T, Dente C, Potter B, Kirk A, Elster E. The Uniformed Services University’s Surgical Critical Care Initiative (SC2i): Bringing Precision Medicine to the Critically Ill. Military Medicine 2018;183(suppl_1):487 View
- Belard A, Buchman T, Forsberg J, Potter B, Dente C, Kirk A, Elster E. Precision diagnosis: a view of the clinical decision support systems (CDSS) landscape through the lens of critical care. Journal of Clinical Monitoring and Computing 2017;31(2):261 View
- Rittmann B, Stevens M. Clinical Decision Support Systems and Their Role in Antibiotic Stewardship: a Systematic Review. Current Infectious Disease Reports 2019;21(8) View
- Ruminski C, Clark M, Lake D, Kitzmiller R, Keim-Malpass J, Robertson M, Simons T, Moorman J, Calland J. Impact of predictive analytics based on continuous cardiorespiratory monitoring in a surgical and trauma intensive care unit. Journal of Clinical Monitoring and Computing 2019;33(4):703 View
- Harrison A, Herasevich V, Gajic O. Automated Sepsis Detection, Alert, and Clinical Decision Support. Critical Care Medicine 2015;43(8):1776 View
- Celi L, Marshall J, Lai Y, Stone D. Disrupting Electronic Health Records Systems: The Next Generation. JMIR Medical Informatics 2015;3(4):e34 View
- Sebat C, Sinigayan V, Albertson T. Hospital Rapid Response Systems. Hospital Medicine Clinics 2017;6(4):480 View
- Wellner B, Grand J, Canzone E, Coarr M, Brady P, Simmons J, Kirkendall E, Dean N, Kleinman M, Sylvester P. Predicting Unplanned Transfers to the Intensive Care Unit: A Machine Learning Approach Leveraging Diverse Clinical Elements. JMIR Medical Informatics 2017;5(4):e45 View
- Peiffer-Smadja N, Rawson T, Ahmad R, Buchard A, Georgiou P, Lescure F, Birgand G, Holmes A. Machine learning for clinical decision support in infectious diseases: a narrative review of current applications. Clinical Microbiology and Infection 2020;26(5):584 View
- Khazaei H, McGregor C, Eklund J, El-Khatib K. Real-Time and Retrospective Health-Analytics-as-a-Service: A Novel Framework. JMIR Medical Informatics 2015;3(4):e36 View
- Beeksma M, Verberne S, van den Bosch A, Das E, Hendrickx I, Groenewoud S. Predicting life expectancy with a long short-term memory recurrent neural network using electronic medical records. BMC Medical Informatics and Decision Making 2019;19(1) View
- Berger J, Valera E, Jankelow A, Garcia C, Akhand M, Heredia J, Ghonge T, Liu C, Font-Bartumeus V, Oshana G, Tiao J, Bashir R. Simultaneous electrical detection of IL-6 and PCT using a microfluidic biochip platform. Biomedical Microdevices 2020;22(2) View
- Bradley R, Tagkopoulos I, Kim M, Kokkinos Y, Panagiotakos T, Kennedy J, De Meyer G, Watson P, Elliott J. Predicting early risk of chronic kidney disease in cats using routine clinical laboratory tests and machine learning. Journal of Veterinary Internal Medicine 2019;33(6):2644 View
- Sakib N, Ahamed S, Khan R, Griffin P, Haque M. Unpacking Prevalence and Dichotomy in Quick Sequential Organ Failure Assessment and Systemic Inflammatory Response Syndrome Parameters: Observational Data–Driven Approach Backed by Sepsis Pathophysiology. JMIR Medical Informatics 2020;8(12):e18352 View
- Schwartz J, Moy A, Rossetti S, Elhadad N, Cato K. Clinician involvement in research on machine learning–based predictive clinical decision support for the hospital setting: A scoping review. Journal of the American Medical Informatics Association 2021;28(3):653 View
- Chicco D, Oneto L. Data analytics and clinical feature ranking of medical records of patients with sepsis. BioData Mining 2021;14(1) View
- Fenner B, Darden D, Kelly L, Rincon J, Brakenridge S, Larson S, Moore F, Efron P, Moldawer L. Immunological Endotyping of Chronic Critical Illness After Severe Sepsis. Frontiers in Medicine 2021;7 View
- Anahtar M, Yang J, Kanjilal S, McAdam A. Applications of Machine Learning to the Problem of Antimicrobial Resistance: an Emerging Model for Translational Research. Journal of Clinical Microbiology 2021;59(7) View
- Giordano C, Brennan M, Mohamed B, Rashidi P, Modave F, Tighe P. Accessing Artificial Intelligence for Clinical Decision-Making. Frontiers in Digital Health 2021;3 View
- Park J, Hsu T, Hu J, Chen C, Hsu W, Lee M, Ho J, Lee C. Predicting Sepsis Mortality in a Population-Based National Database: Machine Learning Approach. Journal of Medical Internet Research 2022;24(4):e29982 View
- Bacchi S, Tan Y, Oakden‐Rayner L, Jannes J, Kleinig T, Koblar S. Machine learning in the prediction of medical inpatient length of stay. Internal Medicine Journal 2022;52(2):176 View
- Bishop J, Javed H, el-Bouri R, Zhu T, Taylor T, Peto T, Watkinson P, Eyre D, Clifton D, Chen T. Improving patient flow during infectious disease outbreaks using machine learning for real-time prediction of patient readiness for discharge. PLOS ONE 2021;16(11):e0260476 View
- Zhang H. Analytical Solution to a Discrete-Time Model for Dynamic Learning and Decision Making. Management Science 2022;68(8):5924 View
- Ocampo-Quintero N, Vidal-Cortés P, del Río Carbajo L, Fdez-Riverola F, Reboiro-Jato M, Glez-Peña D. Enhancing sepsis management through machine learning techniques: A review. Medicina Intensiva (English Edition) 2022;46(3):140 View
- Rosenstrom E, Meshkinfam S, Ivy J, Goodarzi S, Capan M, Huddleston J, Romero-Brufau S. Optimizing the First Response to Sepsis: An Electronic Health Record-Based Markov Decision Process Model. Decision Analysis 2022;19(4):265 View
- Liang D, Deng H, Liu Y. The treatment of sepsis: an episodic memory-assisted deep reinforcement learning approach. Applied Intelligence 2023;53(9):11034 View
- Jazayeri A, Capan M, Ivy J, Arnold R, Yang C. Proximity of Cellular and Physiological Response Failures in Sepsis. IEEE Journal of Biomedical and Health Informatics 2021;25(11):4089 View
- Kokkinos Y, Morrison J, Bradley R, Panagiotakos T, Ogeer J, Chew D, O’Flynn C, De Meyer G, Watson P, Tagkopoulos I. An early prediction model for canine chronic kidney disease based on routine clinical laboratory tests. Scientific Reports 2022;12(1) View
- Parra-Rodriguez L, Guillamet M. Antibiotic Decision-Making in the ICU. Seminars in Respiratory and Critical Care Medicine 2022;43(01):141 View
- Ali T, Ahmed S, Aslam M. Artificial Intelligence for Antimicrobial Resistance Prediction: Challenges and Opportunities towards Practical Implementation. Antibiotics 2023;12(3):523 View
- Liu R, Hunold K, Caterino J, Zhang P. Estimating treatment effects for time-to-treatment antibiotic stewardship in sepsis. Nature Machine Intelligence 2023;5(4):421 View
- Machado J, Rodrigues C, Sousa R, Gomes L. Drug–drug interaction extraction‐based system: An natural language processing approach. Expert Systems 2025;42(1) View
- Barrett C, Suzuki Y, Hussein S, Garg L, Tumolo A, Sandhu A, West J, Zipse M, Aleong R, Varosy P, Tzou W, Banaei‐Kashani F, Rosenberg M. Evaluation of Quantitative Decision‐Making for Rhythm Management of Atrial Fibrillation Using Tabular Q‐Learning. Journal of the American Heart Association 2023;12(9) View
- Otten M, Jagesar A, Dam T, Biesheuvel L, den Hengst F, Ziesemer K, Thoral P, de Grooth H, Girbes A, François-Lavet V, Hoogendoorn M, Elbers P. Does Reinforcement Learning Improve Outcomes for Critically Ill Patients? A Systematic Review and Level-of-Readiness Assessment. Critical Care Medicine 2024;52(2):e79 View
- Hempel L, Sadeghi S, Kirsten T. Prediction of Intensive Care Unit Length of Stay in the MIMIC-IV Dataset. Applied Sciences 2023;13(12):6930 View
- Zhang Y, Xu W, Yang P, Zhang A. Machine learning for the prediction of sepsis-related death: a systematic review and meta-analysis. BMC Medical Informatics and Decision Making 2023;23(1) View
- Tuli F, Varghese A, Ande J. Data-Driven Decision Making: A Framework for Integrating Workforce Analytics and Predictive HR Metrics in Digitalized Environments. Global Disclosure of Economics and Business 2018;7(2):109 View
- Atwal K. Artificial intelligence in clinical nutrition and dietetics: A brief overview of current evidence. Nutrition in Clinical Practice 2024;39(4):736 View
- Basile L, Carbonara N, Panniello U, Pellegrino R. The role of big data analytics in improving the quality of healthcare services in the Italian context: The mediating role of risk management. Technovation 2024;133:103010 View
- Singh P, Singh S, Mishra A, Mishra S. Multimodality treatment planning using the Markov decision process: a comprehensive study of applications and challenges. Research on Biomedical Engineering 2024;40(2):435 View
- Dai M, Jian Y, Zhao X, Wang Y, Zhou B. The simulation and application of large depth of field 3D points reconstruction based on PSF and MOGA improved network. Optics and Lasers in Engineering 2024;181:108383 View
- Nikravangolsefid N, Reddy S, Truong H, Charkviani M, Ninan J, Prokop L, Suppadungsuk S, Singh W, Kashani K, Garces J. Machine learning for predicting mortality in adult critically ill patients with Sepsis: A systematic review. Journal of Critical Care 2024;84:154889 View
- Cocker D, Birgand G, Zhu N, Rodriguez-Manzano J, Ahmad R, Jambo K, Levin A, Holmes A. Healthcare as a driver, reservoir and amplifier of antimicrobial resistance: opportunities for interventions. Nature Reviews Microbiology 2024;22(10):636 View
Books/Policy Documents
- Sethi T. Guide to Big Data Applications. View
- Utomo C, Kurniawati H, Li X, Pokharel S. Advanced Data Mining and Applications. View
- Cox L, Popken D, Sun R. Causal Analytics for Applied Risk Analysis. View
- Tegenaw G, Amenu D, Ketema G, Verbeke F, Cornelis J, Jansen B. Wireless Mobile Communication and Healthcare. View
- Wang R, Liu J, Chen Z, Gong M, Li C, Guo W. Artificial Intelligence in Medicine. View
- Acharjee A, Kumar S, Acharjee P, Ball G. Emerging Paradigms for Antibiotic-Resistant Infections: Beyond the Pill. View