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Artificial Intelligence in Clinical and Surgical Gynecology

Sayı: 21 5 Ocak 2024
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Artificial Intelligence in Clinical and Surgical Gynecology

Öz

Clinicians have increasingly been using artificial intelligence (AI) to make decisions and to increase their knowledge in various clinical and surgical gynecological areas. A vast amount of clinical, medical, and biological patient data is processed in fast computer networks using complex algorithms to create mathematical modeling. The development of these mathematical models gives hope of a promising future with their contribution to overcoming the difficulties encountered in the diagnosis, individualization of treatment plans and improving patient outcomes. Virtual AI in clinical gynecology uses pattern recognition to aid diagnosis, plan treatment, and predict outcomes in gynecological malignancies, assisted reproductive techniques, and urogynecology. In gynecological surgery, physical AI combines augmented reality in operations in the form of computer-aided or robotic platforms. However, AI is yet to be fully incorporated into modern medical practice to improve patient outcomes in clinical gynecology.

Anahtar Kelimeler

Destekleyen Kurum

Yok

Kaynakça

  1. 1. KLAS: Artificial Intelligence Success Requires Partnership, Training. http://healthitanalytics.com/news/klas-artificial-intelligence-success-requires-partnership-training 2019 .Jan 2020
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  3. 3. Cavalera F, Zanoni M, Merico V, et al. Neural network-based identification of developmentally competent or incompetent mouse fully-grown oocytes. Journal of Visualized Experiments. 2018;133:56668.
  4. 4. Goodson SG, White S, Stevans AM, Bhat S, et al. CASAnova: A multiclass support vector machine model for the classification of human sperm motility patterns. Biology of Reproduction. 2017;97(5):698–708.
  5. 5. Girela JL, Gil D, Johnsson M, Gomez-Torres MJ, Juan JD. Semen parameters can be predicted from environmental factors and lifestyle using artificial intelligence methods. Biology of Reproduction. 2013;88(4):99.
  6. 6. Akınsal EA, Haznedar B, Baydilli N, Kalinli A, Oztürk A, Ekmekçioğlu O. Artificial neural network for the prediction of chromosomal abnormalities in azoospermic males. Urology Journal. 2018;15(3):122-125.
  7. 7. Saeedi P, Yee D, Au J, Havelock J. Automatic identification of human blastocyst components via texture. IEEE Transactions on Bio-Medical Engineering. 2017;64(12):2968–2978.
  8. 8. Bendus AEB, Mayer JF, Shipley SK, Catherino WH. Interobserver and intraobserver variation in day 3 embryo grading. Fertility and Sterility. 2006;86(6):1608–1615.

Ayrıntılar

Birincil Dil

İngilizce

Konular

Klinik Tıp Bilimleri

Bölüm

Derleme

Erken Görünüm Tarihi

8 Ocak 2024

Yayımlanma Tarihi

5 Ocak 2024

Gönderilme Tarihi

2 Mayıs 2023

Kabul Tarihi

5 Aralık 2023

Yayımlandığı Sayı

Yıl 2023 Sayı: 21

Kaynak Göster

APA
Polat, G., & Arslan, H. K. (2024). Artificial Intelligence in Clinical and Surgical Gynecology. Istanbul Gelisim University Journal of Health Sciences, 21, 1232-1241. https://doi.org/10.38079/igusabder.1291375
AMA
1.Polat G, Arslan HK. Artificial Intelligence in Clinical and Surgical Gynecology. IGUSABDER. 2024;(21):1232-1241. doi:10.38079/igusabder.1291375
Chicago
Polat, Gülseren, ve Hatice Kübra Arslan. 2024. “Artificial Intelligence in Clinical and Surgical Gynecology”. Istanbul Gelisim University Journal of Health Sciences, sy 21: 1232-41. https://doi.org/10.38079/igusabder.1291375.
EndNote
Polat G, Arslan HK (01 Ocak 2024) Artificial Intelligence in Clinical and Surgical Gynecology. Istanbul Gelisim University Journal of Health Sciences 21 1232–1241.
IEEE
[1]G. Polat ve H. K. Arslan, “Artificial Intelligence in Clinical and Surgical Gynecology”, IGUSABDER, sy 21, ss. 1232–1241, Oca. 2024, doi: 10.38079/igusabder.1291375.
ISNAD
Polat, Gülseren - Arslan, Hatice Kübra. “Artificial Intelligence in Clinical and Surgical Gynecology”. Istanbul Gelisim University Journal of Health Sciences. 21 (01 Ocak 2024): 1232-1241. https://doi.org/10.38079/igusabder.1291375.
JAMA
1.Polat G, Arslan HK. Artificial Intelligence in Clinical and Surgical Gynecology. IGUSABDER. 2024;:1232–1241.
MLA
Polat, Gülseren, ve Hatice Kübra Arslan. “Artificial Intelligence in Clinical and Surgical Gynecology”. Istanbul Gelisim University Journal of Health Sciences, sy 21, Ocak 2024, ss. 1232-41, doi:10.38079/igusabder.1291375.
Vancouver
1.Gülseren Polat, Hatice Kübra Arslan. Artificial Intelligence in Clinical and Surgical Gynecology. IGUSABDER. 01 Ocak 2024;(21):1232-41. doi:10.38079/igusabder.1291375

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