Page 16 - ITPS-8-3
P. 16
INNOSC Theranostics and
Pharmacological Sciences AI in medical device safety
25. Melani R, Samodra G, Al-Hakim R. Enhancing paediatric doi: 10.3389/fcvm.2024.1432876
diabetes management: How artificial intelligence is 35. Pantanowitz L, Hanna M, Pantanowitz J, et al. Regulatory
revolutionising care. J Gen Health Pharm Sci Res. aspects of artificial intelligence and machine learning. Mod
2024;2(2):36-47. Pathol. 2024;37(12):100609.
doi: 10.57213/tjghpsr.v2i2.378
doi: 10.1016/j.modpat.2024.100609
26. Ahn J, Choi M. Advancements and turning point of artificial 36. Aguilar C, Pacilè S, Weber N, Fillard P. Monitoring
intelligence in ophthalmology: A comprehensive analysis methodology for an AI tool for breast cancer screening
of research trends and collaborative networks. Ophthalmic deployed in clinical centers. Life. 2023;13(2):440.
Physiol Opt. 2024;44(5):1031-1040.
doi: 10.3390/life13020440
doi: 10.1111/opo.13315
37. Harer J. Post-Market Surveillance and Vigilance on the
27. Nambi NH. The use of AI in enhancing patient safety. Res European Market. In: Baumgartner C, Harer J, Schröttner J,
Output J Public Health Med. 2024;3(2):34-37. editors. Medical Devices and in Vitro Diagnostics. Reference
doi: 10.59298/ROJPHM/2024/323437 Series in Biomedical Engineering. Cham: Springer; 2023.
p. 1-39.
28. Rana MS, Shuford J. AI in healthcare: Transforming patient
care through predictive analytics and decision support doi: 10.1007/978-3-030-98743-5_22-1
systems. J Artif Intell Gen Sci. 2024;1(1). 38. Tillu R, Muthusubramanian M, Periyasamy V. Transforming
doi: 10.60087/jaigs.v1i1.30 regulatory reporting with AI/ML: Strategies for compliance
and efficiency. J Knowl Learn Sci Technol. 2023;2(1):145-157.
29. Keim-Malpass J, Moorman LP. Nursing and precision
predictive analytics monitoring in the acute and intensive doi: 10.60087/jklst.vol2.n1.p157
care setting: An emerging role for responding to COVID-19 39. RandeepRaj R, Divya P, Susmita A, Sushmitha P, Ramya CH,
and beyond. Int J Nurs Stud Adv. 2021;3:100019. Chandini K. Automation in pharmacovigilance: Artificial
doi: 10.1016/j.ijnsa.2021.100019 intelligence and machine learning for patient safety. J Innov
Appl Pharm Sci. 2022;118-122.
30. Tong L, Luo J, Cisler R, Cantor M. Machine Learning-Based
Modeling of Big Clinical Trials Data for Adverse Outcome doi: 10.37022/jiaps.v7i3.374
Prediction: A Case Study of Death Events. In: 2019 IEEE 40. Desai MK. Artificial intelligence in pharmacovigilance
43 Annual Computer Software and Applications Conference – Opportunities and challenges. Perspect Clin Res.
rd
(COMPSAC). Milwaukee, WI, USA; 2019. p. 269-274. 2024;15(3):116-121.
doi: 10.1109/COMPSAC.2019.10218 doi: 10.4103/picr.picr_290_23
31. Akinola O, Akinola A, Victor Ifeanyi I, et al. Artificial 41. Dwivedi DN, Mahanty G, Dwivedi VN. ChatGPT and AI in
intelligence and machine learning techniques for anomaly government: Pioneering real-time data-driven strategies. In:
detection and threat mitigation in cloud-connected medical Sharma P, et al., editors. Real-Time Data Decisions with AI
devices. Int J Innov Sci Res Technol. 2024;3:1886-1898. and ChatGPT Techniques. United States: IGI Global; 2024.
p. 47-68.
doi: 10.38124/ijisrt/ijisrt24mar1231
doi: 10.4018/979-8-3693-2284-0.ch003
32. Singh S, Kumar R, Payra S, et al. Artificial intelligence
and machine learning in pharmacological research: 42. Giachino C, Cepel M, Truant E, Bargoni A. Artificial
Bridging the gap between data and drug discovery. Cureus. intelligence-driven decision making and firm performance:
2023;15(8):e44359. A quantitative approach. Manage Decis. 2024.
doi: 10.7759/cureus.44359 doi: 10.1108/MD-10-2023-1966
33. Vidi VD, Matheny ME, Donnelly S, Resnic FS. An 43. Olawade DB, Aderinto N, Olatunji G, Kokori E, David-
evaluation of a distributed medical device safety surveillance Olawade AC, Hadi M. Advancements and applications of
system: The DELTA network study. Contemp Clin Trials. Artificial Intelligence in cardiology: Current trends and
2011;32(3):309-317. future prospects. J Med Surg Public Health. 2024;3:100109.
doi: 10.1016/j.cct.2011.02.001 doi: 10.1016/j.glmedi.2024.100109
44. Tran MT. Unlocking the AI-powered customer experience:
34. Papalamprakopoulou Z, Stavropoulos D, Moustakidis
S, Avgerinos D, Efremidis M, Kampaktsis PN. Artificial Personalized service, enhanced engagement, and data-
intelligence-enabled atrial fibrillation detection using driven strategies for e-commerce applications. J Infrastruct
smartwatches: Current status and future perspectives. Front Policy Dev. 2024;8(7):4970.
Cardiovasc Med. 2024;11:1432876. 45. Kothapalli S, Appavu R. The application of artificial
Volume 8 Issue 3 (2025) 10 doi: 10.36922/itps.6204

