Publications by authors named "A M Hagag"
Background/objectives: Adaptive optics ophthalmoscopy (AOO) has the potential to provide insights into AMD pathology and to assess the risk of progression. We aim to utilise AOO to describe detailed features of intermediate AMD and to characterise microscopic changes during atrophy development.
Subjects/methods: Patients with intermediate AMD were recruited into PINNACLE, a prospective observational cohort study.
Background: This research aims to improve glioblastoma survival prediction by integrating MR images, clinical, and molecular-pathologic data in a transformer-based deep learning model, addressing data heterogeneity and performance generalizability.
Methods: We propose and evaluate a transformer-based nonlinear and nonproportional survival prediction model. The model employs self-supervised learning techniques to effectively encode the high-dimensional MRI input for integration with nonimaging data using cross-attention.
Article Synopsis
- - The study presents a deep learning system aimed at speeding up the identification of new biomarkers for age-related macular degeneration (AMD) using a large dataset of retinal OCT images from 3,456 adults aged 51-102 years.
- - A neural network trained with self-supervised learning identified features in 46,496 OCT images, which were then categorized into 30 clusters to help specialists assign clinical meanings to these features.
- - The results showed that 27 out of 30 clusters had distinct characteristics related to AMD, with 7 corresponding to established biomarkers and 16 potentially representing new or recent biomarker combinations not currently used in grading systems.
Evaluating AI models in head and neck cancer research: the use of NCI data by ChatGPT 3.5, ChatGPT 4.0, Google Bard, and Bing Chat.
Oral Surg Oral Med Oral Pathol Oral Radiol
September 2024
This article aims to explore the integration of ChatGPT, an advanced conversational artificial intelligence model, in the field of dentistry. The review primarily consists of information related to the capabilities and functionalities of ChatGPT and how these abilities can aid dental professionals. This study includes data from research papers, case studies, and relevant literature on language models, as well as papers on dentistry, patient communication, dental education, and clinical decision-making.
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