Publications by authors named "Marwan H Aljohani"

Article Synopsis
  • This study evaluated the quality of dental information produced by ChatGPT, focusing on areas like oral surgery, preventive dentistry, and oral cancer, using a standardized scoring system based on accuracy, clarity, and comprehensibility.
  • ChatGPT performed best in preventive dentistry with a score of 4.3/5 but showed lower accuracy in oral surgery (3.9/5) and oral cancer (3.6/5), highlighting gaps in post-operative guidance and risk assessments.
  • The results emphasize the importance of professional oversight when using AI for dental information, advising caution to ensure it's used responsibly and effectively in patient care.
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Objectives: Medication-related osteonecrosis of the jaw (MRONJ) is a significant complication associated with bisphosphonates, impacting jaw osteoclasts, and causing altered bone remodelling. Prevention involves stabilizing systemic pathology, considering antiresorptive therapies, and exploring platelet-rich fibrin (PRF) for wound healing and tissue regeneration. The study aims to assess the efficacy of PRF in MRONJ treatment and highlight research gaps for more robust investigations.

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Aims: This study aimed to assess the awareness of the risk of medication-related osteonecrosis of the jaw (MRONJ) among general dental practitioners (GDPs) and primary care physicians (PCPs), focusing on the clinical implications and coordination of treating or identifying high-risk patients.

Materials And Methods: Two Google Forms electronic questionnaires were distributed to 724 GDPs and 617 PCPs in primary care settings. One for PCPs with eight multiple choice questions and the other for GDPs with 10 multiple choice questions.

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Objectives: To establish local DRL (LDRL) for computed tomography (CT) examinations based on size-specific dose estimates (SSDEs), which consider patient size. The concept of diagnostic reference level (DRL) was introduced to limit patient exposure to unnecessary radiation. However, traditional DRL values do not consider patient size.

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