Martin SS, Aday AW, Almarzooq ZI, Anderson CAM, Arora P, Avery CL, et al. Heart disease and stroke statistics: a report of US and global data from the American heart association. Circulation. 2024. https://doi.org/10.1161/cir.0000000000001209.

Article  Google Scholar 

Pramono A, Setyawan YB, Chayati N, Widyastuti Y, Azizah S. Risk factors for cardiac arrest in the intensive care unit (ICU). AIP Conf Proc. 2024;3165:070003. https://doi.org/10.1063/5.0218028.

Article  Google Scholar 

Fu LH, Schwartz J, Moy A, Knaplund C, Kang MJ, Schnock KO, et al. Development and validation of early warning score system: A systematic literature review. J Biomed Inform. 2020;105:103410. https://doi.org/10.1016/j.jbi.2020.103410.

Article  Google Scholar 

Bleyer AJ, Vidya S, Russell GB, Jones CM, Sujata L, Daeihagh P, et al. Longitudinal analysis of one million vital signs in patients in an academic medical center. Resuscitation. 2011;82(11):1387–92. https://doi.org/10.1016/j.resuscitation.2011.06.033.

Article  Google Scholar 

Hillman K, Bristow P, Chey T, Daffurn K, Jacques T, Norman S, et al. Duration of life-threatening antecedents prior to intensive care admission. Intensive Care Med. 2002;28(11):1629–34. https://doi.org/10.1007/s00134-002-1496-y.

Article  Google Scholar 

Kause J, Smith G, Prytherch D, Parr M, Flabouris A, Hillman K. A comparison of antecedents to cardiac arrests, deaths and emergency intensive care admissions in Australia and New Zealand, and the United Kingdom—the ACADEMIA study. Resuscitation. 2004;62(3):275–82. https://doi.org/10.1016/j.resuscitation.2004.05.016.

Article  Google Scholar 

Downey CL, Tahir W, Randell R, Brown JM, Jayne DG. Strengths and limitations of early warning scores: a systematic review and narrative synthesis. Int J Nurs Stud. 2017;76:106–19. https://doi.org/10.1016/j.ijnurstu.2017.09.003.

Article  Google Scholar 

Alam N, Hobbelink EL, Van Tienhoven AJ, Van De Ven PM, Jansma EP, Nanayakkara PWB. The impact of the use of the Early Warning Score (EWS) on patient outcomes: a systematic review. Resuscitation. 2014;85(5):587–94. https://doi.org/10.1016/j.resuscitation.2014.01.013.

Article  Google Scholar 

Hogan H, Healey F, Neale G, Thomson R, Vincent C, Black N. Preventable deaths due to problems in care in English acute hospitals: a retrospective case record review study. BMJ Qual Saf. 2012;21(9):737–45. https://doi.org/10.1136/bmjqs-2011-001159.

Article  Google Scholar 

Cei M, Bartolomei C, Mumoli N. In-hospital mortality and morbidity of elderly medical patients can be predicted at admission by the Modified Early Warning Score: a prospective study. Int J Clin Pract. 2009;63(4):591–5. https://doi.org/10.1111/j.1742-1241.2008.01986.x.

Article  Google Scholar 

De Meester K, Das T, Hellemans K, Verbrugghe W, Jorens PG, Verpooten GA, et al. Impact of a standardized nurse observation protocol including MEWS after intensive care unit discharge. Resuscitation. 2012;84(2):184–8. https://doi.org/10.1016/j.resuscitation.2012.06.017.

Article  Google Scholar 

Paterson R, MacLeod D, Thetford D, Beattie A, Graham C, Lam S, et al. Prediction of in-hospital mortality and length of stay using an early warning scoring system: clinical audit. Clin Med. 2006;6(3):281–4. https://doi.org/10.7861/clinmedicine.6-3-281.

Article  Google Scholar 

Moon A, Cosgrove JF, Lea D, Fairs A, Cressey DM. An eight year audit before and after the introduction of modified early warning score (MEWS) charts, of patients admitted to a tertiary referral intensive care unit after CPR. Resuscitation. 2010;82(2):150–4. https://doi.org/10.1016/j.resuscitation.2010.09.480.

Article  Google Scholar 

Ridley S. The recognition and early management of critical illness. Ann Royal Coll Surg Engl. 2005;87(5):315–22. https://doi.org/10.1308/003588405x60669.

Article  Google Scholar 

Jayasundera R, Neilly M, Smith T, Myint P. Are early warning scores useful predictors for mortality and morbidity in hospitalised acutely unwell older patients? A systematic review. J Clin Med. 2018;7(10):309. https://doi.org/10.3390/jcm7100309.

Article  Google Scholar 

Yoo JW, Lee JR, Jung YK, Choi SH, Son JS, Kang BJ, et al. A combination of early warning score and lactate to predict intensive care unit transfer of inpatients with severe sepsis/septic shock. Korean J Intern Med. 2015;30(4):471. https://doi.org/10.3904/kjim.2015.30.4.471.

Article  Google Scholar 

Liljehult J, Christensen T. Early warning score predicts acute mortality in stroke patients. Acta Neurol Scand. 2015;133(4):261–7. https://doi.org/10.1111/ane.12452.

Article  Google Scholar 

Huggan PJ, Akram F, Er BHD, Christen LSJ, Weixian L, Lim V, et al. Measures of acute physiology, comorbidity and functional status to differentiate illness severity and length of stay among acute general medical admissions: a prospective cohort study. Intern Med J. 2015;45(7):732–40. https://doi.org/10.1111/imj.12795.

Article  Google Scholar 

Morgan R, Lloyd-Williams F, Wright M, Morgan-Warren R. An early warning scoring system for detecting developing critical illness [Internet]. 1997 [cited 2025 Jan 17]. Available from: https://www.semanticscholar.org/paper/An-early-warning-scoring-system-for-detecting-Morgan-Lloyd-Williams/5d7dd63a226927e2f5558787f851c9ec67d3558c.

Subbe CP, Kruger M, Rutherford P, Gemmel L. Validation of a modified Early Warning Score in medical admissions. QJM. 2001;94(10):521–6. https://doi.org/10.1093/qjmed/94.10.521.

Article  Google Scholar 

García-Del-Valle S, Arnal-Velasco D, Molina-Mendoza R, Gómez-Arnau JI. Update on early warning scores. Best Pract Res Clin Anaesthesiol. 2021;35(1):105–13. https://doi.org/10.1016/j.bpa.2020.12.013.

Article  Google Scholar 

Sefton G, Lane S, Killen R, Black S, Lyon M, Ampah P, et al. Accuracy and efficiency of recording pediatric early warning scores using an electronic physiological surveillance system compared with traditional Paper-Based documentation. CIN Comput Inf Nurs. 2016;35(5):228–36. https://doi.org/10.1097/cin.0000000000000305.

Article  Google Scholar 

Swapna M, Viswanadhula UM, Aluvalu R, Vardharajan V, Kotecha K. Bio-Signals in medical applications and challenges using artificial intelligence. J Sens Actuator Netw. 2022;11(1):17. https://doi.org/10.3390/jsan11010017.

Article  Google Scholar 

Lee YJ, Park C, Kim H, Cho SJ, Yeo WH. Artificial intelligence on biomedical signals: technologies, applications, and future directions. Med-X. 2024. https://doi.org/10.1007/s44258-024-00043-1.

Article  Google Scholar 

Bio-signal processing and classification using computational learning and intelligence [Internet]. In: Elsevier eBooks. 2022. Available from: https://doi.org/10.1016/c2019-0-00985-5.

Rasheed K, Qayyum A, Qadir J, Sivathamboo S, Kwan P, Kuhlmann L, et al. Machine learning for predicting epileptic seizures using EEG signals: a review. IEEE Rev Biomed Eng. 2020;13(14):139–55. https://doi.org/10.1109/rbme.2020.3008792.

Article  Google Scholar 

Petmezas G, Haris K, Stefanopoulos L, Kilintzis V, Tzavelis A, Rogers JA, et al. Automated atrial fibrillation detection using a Hybrid CNN-LSTM network on imbalanced ECG datasets. Biomed Signal Process Control. 2020;8(63):102194. https://doi.org/10.1016/j.bspc.2020.102194.

Article  Google Scholar 

Pandey SK, Janghel RR, Vani V. Patient specific machine learning models for ECG signal classification. Proc Comput Sci. 2020;1(167):2181–90. https://doi.org/10.1016/j.procs.2020.03.269.

Article  Google Scholar 

Kim H, Lee YJ, Byun G, Choi C, Yeo W. Advances in ultrathin soft sensors, integrated materials, and manufacturing technologies for enhanced monitoring of human physiological signals. Adv Electron Mater. 2023. https://doi.org/10.1002/aelm.202201294.

Article  Google Scholar 

Yang K, Meadmore K, Freeman C, Grabham N, Hughes AM, Wei Y, et al. Development of User-Friendly wearable electronic textiles for healthcare applications. Sensors. 2018;18(8):2410. https://doi.org/10.3390/s18082410.

Article  Google Scholar 

Mantini D, Marzetti L, Corbetta M, Romani GL, Del Gratta C. Multimodal integration of FMRI and EEG data for high spatial and temporal resolution analysis of brain networks. Brain Topogr. 2010;23(2):150–8. https://doi.org/10.1007/s10548-009-0132-3.

Article  Google Scholar 

Churpek MM, Yuen TC, Huber MT, Park SY, Hall JB, Edelson DP. Predicting cardiac arrest on the wards. Chest J. 2011;141(5):1170–6. https://doi.org/10.1378/chest.11-1301.

Article  Google Scholar 

Green M, Lander H, Snyder A, Hudson P, Churpek M, Edelson D. Comparison of the Between the Flags calling criteria to the MEWS, NEWS and the electronic Cardiac Arrest Risk Triage (eCART) score for the identification of deteriorating ward patients. Resuscitation. 2017;22(123):86–91. https://doi.org/10.1016/j.resuscitation.2017.10.028.

Article  Google Scholar 

Lyons PG, Edelson DP, Churpek MM. Rapid response systems. Resuscitation. 2018;16(128):191–7. https://doi.org/10.1016/j.resuscitation.2018.05.013.

Article  Google Scholar 

Smith GB, Prytherch DR, Meredith P, Schmidt PE. Early warning scores: unravelling detection and escalation. Int J Health Care Qual Assur. 2015;28(8):872–5. https://doi.org/10.1108/ijhcqa-07-2015-0086.

Article  Google Scholar 

McNeill G, Bryden D. Do either early warning systems or emergency response teams improve hospital patient survival? A systematic review. Resuscitation. 2013;84(12):1652–67. https://doi.org/10.1016/j.resuscitation.2013.08.006.

Article  Google Scholar 

Smith MEB, Chiovaro JC, O’Neil M, Kansagara D, Quiñones AR, Freeman M, et al. Early warning system scores for clinical deterioration in hospitalized patients: a systematic review. Ann Am Thorac Soc. 2014;11(9):1454–65. https://doi.org/10.1513/annalsats.201403-102oc.

Article  Google Scholar 

London RC of PO. National Early Warning Score (NEWS): Standardising the Assessment of Acute-Illness Severity in the NHS. 2012.

National Early Warning Score (NEWS) 2 [Internet]. RCP London. [cited 2025 Jan 17]. Available from: https://www.rcp.ac.uk/improving-care/resources/national-early-warning-score-news-2/.

Monaghan A. Detecting and managing deterioration in children. Paediatr Care. 2005;17(1):32–5.