Publications by authors named "M Nour Alkhatib"

Background: Oral cancer, particularly mucoepidermoid carcinoma (MEC), presents diagnostic challenges due to its histological diversity and rarity. This study aimed to develop machine learning (ML) models to predict survival outcomes for MEC patients and pioneer a clinically accessible prognostic tool.

Methods: Using the SEER database (2000-2020), we constructed predictive models with five ML algorithms: Random Forest Classifier (RFC), Gradient Boosting Classifier (GBC), Logistic Regression (LR), K-Nearest Neighbors (KNN), and Multilayer Perceptron (MLP).

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Objective: Intracranial solitary fibrous tumor is a rare central nervous system tumor that lacks a reliable prognostic clinical model. Uncertainty persists regarding the treatment outcomes of surgery and adjuvant radiotherapy (ART). To address this, we investigated the efficacy of ART and applied machine learning (ML) to develop accurate prognostic models.

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: This study aims to investigate the role of congenital single nucleotide thrombophilia in young females with early recurrent pregnancy loss (RPL). : We studied 120 pregnant females with RPL and 80 matched females as a control with no RPL. Females were aged ≤ 35 years, had at least two consecutive first-trimester RPLs, and the acquired cause of RPL was excluded.

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Background: Adenoid cystic carcinoma (ACC) of the oral cavity is a rare head and neck cancer. This rarity contributes to the paucity of comprehensive research on this cancer thereby complicating the development of evidence-based treatment strategies. This study aims to use machine learning (ML) techniques to analyze survival outcomes and optimize treatment approaches of ACC.

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Objectives: To unravel the still unexplored HBV-replicative kinetics in anti-HBc-positive/HBsAg-negative people-with-HIV (PWH) suspending tenofovir disoproxil-fumarate/tenofovir-alafenamide (TDF/TAF).

Methods: A total of 101 anti-HBc-positive/HBsAg-negative PWH switching to TDF/TAF-sparing therapy were included. Serum HBV-DNA and HBV-RNA were quantified by droplet-digital-PCR at switching (T0), within 12 months (T1) and 12-24 months postswitch (T2).

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