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Breaking the curse of dimensionality: hierarchical Bayesian network model for multi-view clustering

Autor: Salma Jamoussi, Hasna Njah, Walid Mahdi

Publikováno v: Annals of Mathematics and Artificial Intelligence. 89:1013-1033

Clustering high-dimensional data under the curse of dimensionality is an arduous task in many applications domains. The wide dimension yields the complexity-related challenges and the limited number of records leads to the overfitting trap. We propos

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::07f13983789d2b9ac43e4939b78bf867
https://doi.org/10.1007/s10472-021-09749-z

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Using a naive Bayes classifier to explore the factors driving the harmful dinoflagellate Karenia selliformis blooms in a southeastern Mediterranean lagoon

Autor: Nouha Barraj, Asma Hamza, Mabrouka Mahfoudi, Malika Bel Hassen, Hasna Njah, Ahmed Rebai, Wafa Feki-Sahnoun

Publikováno v: Ocean Dynamics. 70:897-911

The blooms of the toxic dinoflagellate Karenia selliformis can be predicted with accuracy derived from knowledge of the main forcing variables. A naive Bayes classifier modeling framework, a member of the Bayesian network family, is used to identify

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::c4807a6ef80da0ad1dce01810418317e
https://doi.org/10.1007/s10236-020-01365-5

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Mitigating Racial Bias in Machine Learning

Autor: Kristin M. Kostick-Quenet, I. Glenn Cohen, Sara Gerke, Bernard Lo, James Antaki, Faezah Movahedi, Hasna Njah, Lauren Schoen, Jerry E. Estep, J.S. Blumenthal-Barby

Publikováno v: The Journal of law, medicineethics : a journal of the American Society of Law, MedicineEthics. 50(1)

When applied in the health sector, AI-based applications raise not only ethical but legal and safety concerns, where algorithms trained on data from majority populations can generate less accurate or reliable results for minorities and other disadvan

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8d5c43d09ce8d2e54109f9059438522c
https://pubmed.ncbi.nlm.nih.gov/35243993

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INFLUENCE OF PHOSPHORUS-CONTAMINATED SEDIMENTS IN THE ABUNDANCE OF POTENTIALLY TOXIC PHYTOPLANKTON ALONG THE SFAX COASTS (GULF OF GABES, TUNISIA)

Autor: Hasna Njah, Mabrouka Mahfoudi, Malika Bel Hassen, Nouha Barraj, Fourat Akrout, Wafa Feki-Sahnoun, Asma Hamza, Ahmed Rebai

Publikováno v: Journal of Sedimentary Environments, Vol 4, Iss 4, Pp 458-470 (2019)

This is the first work performed in the shellfish production area located along the Sfax coasts (southern Tunisia) on the spatial and temporal patterns of toxic phytoplankton. It relates the excessive introduction of phosphorus in coastal waters from

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2c1dbadc5b4141519fb78d055025c757
https://doi.org/10.12957/jse.2019.47324

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A Naïve Bayesian Network Approach to Determine the Potential Drivers of the Toxic Dinoflagellate Coolia monotis in the Gulf of Gabès, Tunisia

Autor: Mabrouka Mahfoudi, Nouha Barraj, Wafa Feki-Sahnoun, Asma Hamza, Hasna Njah, Malika Bel Hassen, Ahmed Rebai, Moufida Abdennadher

Publikováno v: Advances in Science, Technology & Innovation ISBN: 9783319705477

Coolia monotis has occurred recently in many coastal areas of the Gulf of Gabes (South of Tunisia) as potentially toxic marine phytoplankton.

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::26bd2c1c3f873c332b3881cf68644a63
https://doi.org/10.1007/978-3-319-70548-4_178

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Weighted ensemble learning of Bayesian network for gene regulatory networks

Autor: Hasna Njah, Salma Jamoussi

Publikováno v: Neurocomputing. 150:404-416

Gene Regulatory Network (GRN) is known as the most adequate representation of genes׳ interactions based on microarray datasets. One of the most performing modeling tools that enable the inference of these networks is a Bayesian network (BN). When pr

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https://doi.org/10.1016/j.neucom.2014.05.078

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A Bayesian network approach to determine environmental factors controlling Karenia selliformis occurrences and blooms in the Gulf of Gabès, Tunisia

Autor: Ahmed Rebai, Wafa Feki-Sahnoun, Mabrouka Mahfoudi, Malika Bel Hassen, Hasna Njah, Asma Hamza, Nouha Barraj

Publikováno v: Harmful algae. 63

A Bayesian Network modeling framework is introduced to explore the effect of physical and meteorological factors on the dinoflagellate red tide forming Karenia selliformis in various sampling sites of the national phytoplankton monitoring program. Th

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4cf8bf96f3cc2f37240f68acfd1da6ba
https://pubmed.ncbi.nlm.nih.gov/28366386

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A Bayesian approach to construct Context-Specific Gene Ontology: Application to protein function prediction

Autor: Walid Mahdi, Salma Jamoussi, Mohamed Elati, Hasna Njah

Publikováno v: CIBCB

The annotation of protein provides a considerable knowledge for the biologists in order to understand life at the molecular level. The computational annotation of protein function has therefore emerged as an important alternative given that the biolo

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::e347799f91049bbb536fca707be7fe5b
https://doi.org/10.1109/cibcb.2016.7758127

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