Derin Öğrenme ve Makine Öğrenimi Yöntemlerinin Acil Tıptaki Rolü (Referanslar)
Türkiye Acil Tıp Vakfı 4. Uluslararası Acil Tıp Kongresi'ndeki "Derin Öğrenme ve Makine Öğrenimi Yöntemlerinin Acil Tıptaki Rolü" başlıklı sunumumda çeşitli referanslar yer alıyor. Aşağıda bunların bir listesini bulabilirsiniz:
REFERANSLAR
- Adedinsewo D, Carter RE, Attia Z, et al. Artificial Intelligence-Enabled ECG Algorithm to Identify Patients With Left Ventricular Systolic Dysfunction Presenting to the Emergency Department With Dyspnea. Circ Arrhythm Electrophysiol. 2020;13(8):e008437. doi:10.1161/CIRCEP.120.008437
- Al-Dury N, Ravn-Fischer A, Hollenberg J, et al. Identifying the relative importance of predictors of survival in out of hospital cardiac arrest: a machine learning study. Scand J Trauma Resusc Emerg Med. 2020;28(1):60. Published 2020 Jun 25. doi:10.1186/s13049-020-00742-9
- Ambrosino R, Buchanan BG, Cooper GF, Fine MJ. The use of misclassification costs to learn rule-based decision support models for cost-effective hospital admission strategies. Proc Annu Symp Comput Appl Med Care. 1995;304-308.
- Artificial Intelligence and Machine Learning (AI/ML)-Enabled Medical Devices, FDA, https://www.fda.gov/medical-devices/software-medical-device-samd/artificial-intelligence-and-machine-learning-aiml-enabled-medical-devices (opens in a new tab)
- Attia ZI, Noseworthy PA, Lopez-Jimenez F, et al. An artificial intelligence-enabled ECG algorithm for the identification of patients with atrial fibrillation during sinus rhythm: a retrospective analysis of outcome prediction. Lancet. 2019;394(10201):861-867. doi:10.1016/S0140-6736(19)31721-0
- Byrsell F, Claesson A, Ringh M, et al. Machine learning can support dispatchers to better and faster recognize out-of-hospital cardiac arrest during emergency calls: A retrospective study. Resuscitation. 2021;162:218-226. doi:10.1016/j.resuscitation.2021.02.041
- Chin KC, Hsieh TC, Chiang WC, et al. Early recognition of a caller's emotion in out-of-hospital cardiac arrest dispatching: An artificial intelligence approach. Resuscitation. 2021;167:144-150. doi:10.1016/j.resuscitation.2021.08.032
- Elola A, Aramendi E, Rueda E, Irusta U, Wang H, Idris A. Towards the Prediction of Rearrest during Out-of-Hospital Cardiac Arrest. Entropy (Basel). 2020;22(7):758. Published 2020 Jul 9. doi:10.3390/e22070758
- Gafni-Pappas G, Khan M. Predicting daily emergency department visits using machine learning could increase accuracy. Am J Emerg Med. 2023;65:5-11. doi:10.1016/j.ajem.2022.12.019
- Gan RK, Ogbodo JC, Wee YZ, Gan AZ, González PA. Performance of Google bard and ChatGPT in mass casualty incidents triage. Am J Emerg Med. 2024;75:72-78. doi:10.1016/j.ajem.2023.10.034 https://pubmed.ncbi.nlm.nih.gov/37967485/ (opens in a new tab)
- Gilson A, Safranek CW, Huang T, et al. How Does ChatGPT Perform on the United States Medical Licensing Examination (USMLE)? The Implications of Large Language Models for Medical Education and Knowledge Assessment [published correction appears in JMIR Med Educ. 2024 Feb 27;10:e57594. doi: 10.2196/57594]. JMIR Med Educ. 2023;9:e45312. Published 2023 Feb 8. doi:10.2196/45312
- Heidenreich PA, Bozkurt B, Aguilar D, et al. 2022 AHA/ACC/HFSA Guideline for the Management of Heart Failure: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines [published correction appears in Circulation. 2022 May 3;145(18):e1033. doi: 10.1161/CIR.0000000000001073] [published correction appears in Circulation. 2022 Sep 27;146(13):e185. doi: 10.1161/CIR.0000000000001097] [published correction appears in Circulation. 2023 Apr 4;147(14):e674. doi: 10.1161/CIR.0000000000001142]. Circulation. 2022;145(18):e895-e1032. doi:10.1161/CIR.0000000000001063
- Hong N, Cho SW, Shin S, et al. Deep-Learning-Based Detection of Vertebral Fracture and Osteoporosis Using Lateral Spine X-Ray Radiography. J Bone Miner Res. 2023;38(6):887-895. doi:10.1002/jbmr.4814
- Kirubarajan A, Taher A, Khan S, Masood S. Artificial intelligence in emergency medicine: A scoping review. J Am Coll Emerg Physicians Open. 2020 Nov 7;1(6):1691-1702. doi: 10.1002/emp2.12277. PMID: 33392578; PMCID: PMC7771825.
- Nafees Ahmed S, Prakasam P. A systematic review on intracranial aneurysm and hemorrhage detection using machine learning and deep learning techniques. Prog Biophys Mol Biol. 2023;183:1-16. doi:10.1016/j.pbiomolbio.2023.07.001
- Ohu I, Benny PK, Rodrigues S, Carlson JN. Applications of machine learning in acute care research. J Am Coll Emerg Physicians Open. 2020;1(5):766-772. Published 2020 Jul 2. doi:10.1002/emp2.12156
- Otero-Agra M, Jorge-Soto C, Cosido-Cobos ÓJ, et al. Can a voice assistant help bystanders save lives? A feasibility pilot study chatbot in beta version to assist OHCA bystanders. Am J Emerg Med. 2022;61:169-174. doi:10.1016/j.ajem.2022.09.013
- PM Cardio, Powerful Medical. https://www.powerfulmedical.com/pmcardio-individuals/ (opens in a new tab)