Artificial Intelligence in Veterinary Care: A Review of Applications for Animal Health

被引:2
作者
Albadrani, Basima Abdulfatah [1 ]
Abdel-Raheem, M. a. [2 ]
Al-Farwachi, Maab I. [1 ]
机构
[1] Univ Mosul, Coll Vet Med, Dept Internal & Prevent Med, Mosul, Iraq
[2] Agr & Biol Res Inst, Natl Res Ctr, Pests & Plant Protect Dept, Cairo, Egypt
来源
EGYPTIAN JOURNAL OF VETERINARY SCIENCE | 2024年 / 55卷 / 06期
关键词
Artificial intelligence; Veterinary care; Animal Health; Review; Applications; PLATELET-RICH PLASMA; SENSOR; DOGS;
D O I
10.21608/EJVS.2024.260989.1769
中图分类号
S85 [动物医学(兽医学)];
学科分类号
0906 ;
摘要
IN recent years, the application of artificial intelligence (AI) has significantly transformed various industries, including healthcare. Specifically, AI has played a crucial role in enhancing clinical examination, diagnosis, and treatment not only for humans but also for animals. The integration of AI in veterinary medicine has opened doors to accurate and efficient care, benefiting both animals and their owners. This essay will delve into how AI has revolutionized veterinary medicine (Vet Med), highlighting its impact on clinical examinations, diagnosis, and treatment of animals. AIpowered sensors and devices can monitor the vital signs and behaviors of animals in real-time, allowing for early detection of potential health issues. Wearable devices equipped with AI algorithms can track temperature, heart devaluation and diagnosis. In conclusion, AI will facilitate collaboration between practicing veterinarians, commercial AI platform developers and veterinary radiology researchers to optimize the effectiveness and clinical utility of AI in veterinary radiology and ensure the best possible patient care at all times put first.
引用
收藏
页码:1725 / 1736
页数:12
相关论文
共 109 条
  • [51] Curative effect of autologous platelet-rich plasma on a large cutaneous lesion in a dog
    Kim, Jung-Hyun
    Park, Chul
    Park, Hee-Myung
    [J]. VETERINARY DERMATOLOGY, 2009, 20 (02) : 123 - 126
  • [52] King A, 2024, JAVMA-J AM VET MED A, V262, P352, DOI [10.2460/javma.23.08.0429, 10.2460/javma.23.02.0126, 10.1080/00224499.2023.2278528]
  • [53] How to read and review papers on machine learning and artificial intelligence in radiology: a survival guide to key methodological concepts
    Kocak, Burak
    Kus, Ece Ates
    Kilickesmez, Ozgur
    [J]. EUROPEAN RADIOLOGY, 2021, 31 (04) : 1819 - 1830
  • [54] Kour S., 2022, J. Anim. Res., V12, P01, DOI [10.30954/2277-940X.01.2022.1, DOI 10.30954/2277-940X.01.2022.1]
  • [55] Detection of heart rate and rhythm with a smartphone-based electrocardiograph versus a reference standard electrocardiograph in dogs and cats
    Kraus, Marc S.
    Gelzer, Anna R.
    Rishniw, Mark
    [J]. JAVMA-JOURNAL OF THE AMERICAN VETERINARY MEDICAL ASSOCIATION, 2016, 249 (02): : 189 - 194
  • [56] Cardiac monitoring of dogs via smartphone mechanocardiography: a feasibility study
    Lahdenoja, Olli
    Hurnanen, Tero
    Kaisti, Matti
    Koskinen, Juho
    Tuominen, Jarno
    Vaha-Heikkila, Matti
    Parikka, Laura
    Wiberg, Maria
    Koivisto, Tero
    Pankaala, Mikko
    [J]. BIOMEDICAL ENGINEERING ONLINE, 2019, 18
  • [57] Intramammary administration of platelet concentrate as an unconventional therapy in bovine mastitis: First clinical application
    Lange-Consiglio, A.
    Spelta, C.
    Garlappi, R.
    Luini, M.
    Cremonesi, F.
    [J]. JOURNAL OF DAIRY SCIENCE, 2014, 97 (10) : 6223 - 6230
  • [58] Platelet concentrate in bovine reproduction: effects on in vitro embryo production and after intrauterine administration in repeat breeder cows
    Lange-Consiglio, Anna
    Cazzaniga, Nadia
    Garlappi, Rosangela
    Spelta, Chiara
    Pollera, Claudia
    Perrini, Claudia
    Cremonesi, Fausto
    [J]. REPRODUCTIVE BIOLOGY AND ENDOCRINOLOGY, 2015, 13
  • [59] APPROACHES TO MACHINE LEARNING
    LANGLEY, P
    CARBONELL, JG
    [J]. JOURNAL OF THE AMERICAN SOCIETY FOR INFORMATION SCIENCE, 1984, 35 (05): : 306 - 316
  • [60] Overview of Machine Learning: Part 2 Deep Learning for Medical Image Analysis
    Le, William Trung
    Maleki, Farhad
    Romero, Francisco Perdigon
    Forghani, Reza
    Kadoury, Samuel
    [J]. NEUROIMAGING CLINICS OF NORTH AMERICA, 2020, 30 (04) : 417 - +