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An update for various applications of Artificial Intelligence (AI) for detection and identification of marine environmental pollutions: A bibliometric analysis and systematic review.
Zare, Afshin; Ablakimova, Nurgul; Kaliyev, Asset Askerovich; Mussin, Nadiar Maratovich; Tanideh, Nader; Rahmanifar, Farhad; Tamadon, Amin.
  • Zare A; PerciaVista R&D Co. Shiraz, Iran. Electronic address: afshin.zare@bpums.ac.ir.
  • Ablakimova N; Department of Pharmacology, West Kazakhstan Marat Ospanov Medical University, Aktobe 030012, Kazakhstan.
  • Kaliyev AA; Department of Surgery, West Kazakhstan Marat Ospanov Medical University, Aktobe 030012, Kazakhstan.
  • Mussin NM; Department of Surgery, West Kazakhstan Marat Ospanov Medical University, Aktobe 030012, Kazakhstan. Electronic address: nadiar_musin@zkmu.kz.
  • Tanideh N; Stem Cells Technology Research Center, Shiraz University of Medical Sciences, Shiraz 71348-14336, Iran; Department of Pharmacology, Medical School, Shiraz University of Medical Sciences, Shiraz 71348-14336, Iran.
  • Rahmanifar F; Department of Basic Sciences, School of Veterinary Medicine, Shiraz University, Shiraz, Iran.
  • Tamadon A; Department for Natural Sciences, West Kazakhstan Marat Ospanov Medical University, Aktobe, Kazakhstan.
Mar Pollut Bull ; 206: 116751, 2024 Sep.
Article en En | MEDLINE | ID: mdl-39053264
ABSTRACT
Marine environmental pollution is one of the growing concerns of humans all over the world. Therefore, managing these marine pollutants has been a crucial matter for scientists in recent decades. Thus, researchers have tried to implement artificial intelligence (AI) to handle marine environmental pollutants. Therefore, in this manuscript, we performed a bibliometric analysis to understand the main applications of AI for managing marine environments. Therefore, we examined both PubMed online database and Google Scholar to find any research articles that discuss the applications of AI in managing marine environmental pollution. Ultimately, we found that AI can detect, locate, and even predict aquatic contaminants like oil fingerprinting, oil spills, oil spill damage, oil slicks, forecasting marine water quality, water quality development, harmful algal blooms, benthic sediment toxicity, as well as detection of marine debris with high accuracy.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Inteligencia Artificial / Bibliometría / Monitoreo del Ambiente Idioma: En Año: 2024 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Inteligencia Artificial / Bibliometría / Monitoreo del Ambiente Idioma: En Año: 2024 Tipo del documento: Article