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Drought Forecasting: A Bibliometric Analysis and Future Research Directions

Journal of Environmental Protection 2022年第12期13卷 972-990页

作者： Rodrigue B. W. Vodounon henoc soude Ossénatou Mamadou Department of Computer Science Institute of Mathematics and Physics (IMSP) Porto-Novo Benin

Droughts represent one of the most dangerous natural disasters in the world, due to their ability to progressively spread over large areas up to continental scale, as well as their adverse environmental, human and socio-economic effects. Unfortunately, these effects are increasingly accentuated under the influence of climate change. One of the main challenges today is to mitigate the damage associated with droughts by developing tools capable of predicting the occurrence of such events in advance. Many solutions have been implemented for this purpose. But with the great progress in artificial intelligence, many scientists propose the use of Machine Learning to provide more optimal solutions to the problem related to droughts. In the present study, a bibliometric analysis was conducted to assess the current level of research on forecasting and monitoring of droughts in the world in general, particularly in West Africa through different methods based on the artificial intelligence. A search for articles on the topic was performed in the Web of Science (WoS) database, which is a global, publisher-independent citation database. The search identified a total of 3284 documents and the collected data was analyzed using a bibliometric tool called Bibliometrix. The main results are presented and discussed, followed by some potential avenues for research.

关键词： Droughts Forecasting Climate Change Bibliometric Web of Science (WoS)

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Evolution and Trend of Deep Learning in Agriculture: A Bibliometric Approach

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Journal of Computer and Communications 2022年第12期10卷 113-124页

作者： Kimba Sabi N’goye henoc soude Yêyinou Laura Estelle Loko Institute of Mathematics and Physics Porto-Novo Benin High School of Applied Biosciences and Biotechnologies (ENSBBA) Dassa-Zoumé Benin

Deep Learning has recently gained a great deal of attention. From this, resulted many applications in a variety of industries, including agriculture. An essential study goal is to understand what has been done in the use of deep learning in agriculture (DLA) thus far in order to establish a robust research agenda to address its future challenges. The present state of research on the DLA with special attention to Africa was evaluated in this study using bibliometric analysis. A search of documents dealing with DLA was realized in the Web of Science database, a world-leading publisher-independent global citation database. A bibliometric program named Bibliometrix was used to examine the data after the search yielded 3207 items. Key findings are highlighted and discussed, and then some directions for potential future research are suggested.

关键词： Machine Learning Deep Learning Agriculture Bibliometric Africa

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Drought Forecasting: A Bibliometric Analysis and Future Research Directions

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Journal of Environmental Protection（环境保护） 2022年第12期

作者： Rodrigue B. W. Vodounon henoc soude Ossénatou Mamadou

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Comparison of Prognostic Scores for Upper Gastrointestinal Bleeding in the Hepato-Gastro-Enterology Department of Campus Teaching Hospital of Lome

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Open Journal of Gastroenterology 2021年第9期11卷 161-171页

作者： Aklesso Bagny Lidawu Roland-Moïse Kogoe Late Mawuli Lawson-Ananissoh Laconi Yeba Kaaga Debehoma Redah Mawunyo henoc Gbolou Yendoukoa Yves Kanake Departement of Gastroenterology Teaching Hospital Campus of Lome Lome Togo Departement of Gastroenterology University of Lome Lome Togo

Objective: To evaluate and compare the prognostic contribution of different UGIB prognostic scores. Patients and Method: Descriptive cross-sectional study with retrospective collection conducted from January 2014 to December 2019. Patients hospitalized in the Gastroenterology Department of Campus Teaching Hospital of Lome for upper gastrointestinal hemorrhage were included. The analytical component of this study had consisted of an evaluation of the sensitivity and specificity of different prognostic scores (GBS, mGBS, FRS, CRS, AIMS65) in predicting the occurrence of death and/or re-bleeding within 42 days. These different scores were compared using ROC (Receiver Operating Characteristic) curves. Results: We included 314 patients in our study. The male to female sex ratio was 2.48. Fibroscopy found non-related portal hypertension UGIB in 70.94% of the cases. The “FRS” was the most accurate score in predicting death or re-bleeding in all patients. The “FRS” was the most precise score in predicting the occurrence of spotting in all patients. The “FRS” was the most accurate score in predicting death among all patients. The mortality of patients at low risk of death (below the threshold value) was 2.2% for the “FRS”, 9.3% for the “CRS”, 0% for the “GBS” (p = 0.565), 50% for the “mGBS” and 11.4% for the “AIMS65”. Scores were more accurate for non-related portal hypertension UGIB. Conclusion: The “FRS” and the “CRS” are two precise scores in predicting the occurrence of an incident in the event of upper gastrointestinal hemorrhage. However, these scores were less effective in related portal hypertension UGIB.

关键词： Upper Gastrointestinal Bleeding Prognostic Scores Rockall Glas-gow-Blatchford AIMS65 Lome

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Comparison of Prognostic Scores for Upper Gastrointestinal Bleeding in the Hepato-Gastro-Enterology Department of Campus Teaching Hospital of Lome

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Open Journal of Gastroenterology（肠胃病学期刊） 2021年第9期

作者： Aklesso Bagny Lidawu Roland-Moïse Kogoe Late Mawuli Lawson-Ananissoh Laconi Yeba Kaaga Debehoma Redah Mawunyo henoc Gbolou Yendoukoa Yves Kanake

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