Aly Khalifa

A Prescriptive Validation Framework for a Scalable Multi-Layer AI Adoption Model in 6P Medicine

Aly Khalifa, Rada Hussein

The integration of artificial intelligence (AI) into healthcare systems is central to the realization of 6P Medicine that emphasizes Predictive, Preventive, Personalized, Participatory, Precision-oriented, and Public-centered care. While several conceptual AI adoption models have been proposed, few provide prescriptive guidance for real-world …

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EHDS Data Continuum: A Proposed IHE Integration Profile for Bridging Primary and Secondary Health Data Use

Aly Khalifa, Alexander Berler, Rada Hussein

The European Health Data Space (EHDS) aims to enable both the primary use of health data for direct patient care (EHDS1) and the secondary use of data for research, innovation, and public health (EHDS2). While each pillar is supported by distinct infrastructures-MyHealth@EU …

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Artificial Intelligence For 6P Medicine: Consolidating AI Needs of Predictive, Preventive, Personalized, Participatory, Precision, and Public Health Trajectories

Aly Khalifa, Rada Hussein

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A Scalable Multi-Layer AI Adoption Model to Support the Comprehensive Goals of 6P Medicine

Aly Khalifa, Rada Hussein

Developing a scalable multi-layer AI adoption model for 6P medicine (Predictive, Preventive, Personalized, Participatory, Precision-oriented, and Public-centered) requires careful consideration of computational infrastructure, data processing and integration, healthcare-specific requirements, security and privacy, performance optimization, and system interoperability. The described multi-layer architecture in …

us, at (code pays fourni par la source)

Mobgazenet: robust gaze estimation mobile network based on progressive attention mechanisms

Ahmed A. Abdelrahman, Thorsten Hempel, Aly Khalifa, Dominykas Strazdas et autres

Abstract Gaze estimation is a fundamental task in computer vision with a wide range of applications. Recently, convolution neural network approaches have made notable progress in inferring gaze from facial images. However, these methods often struggle to capture fine-grained gaze features and …

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Machine learning automated treatment planning for online magnetic resonance guided adaptive radiotherapy of prostate cancer

Aly Khalifa, Jeff D. Winter, Tony Tadic, Thomas G. Purdie et autres

Background and purpose: No best practices currently exist for achieving high quality radiation therapy (RT) treatment plan adaptation during magnetic resonance (MR) guided RT of prostate cancer. This study validates the use of machine learning (ML) automated RT treatment plan adaptation and …

ca (code pays fourni par la source)

Fine-grained gaze estimation based on the combination of regression and classification losses

Ahmed A. Abdelrahman, Thorsten Hempel, Aly Khalifa, Ayoub K. Al-Hamadi

Abstract Human gaze is a crucial cue used in various applications such as human-robot interaction, autonomous driving, and virtual reality. Recently, convolution neural network (CNN) approaches have made notable progress in predicting gaze angels. However, estimating accurate gaze direction in-the-wild is still …

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9 Machine Learning Plan Adaptation Improves Quality of Ultra-Hypofractionated Adaptive Radiation Therapy for Prostate Cancer On a 1.5T MR-Linear Accelerator

Aly Khalifa, Jeff D. Winter, Tony Tadic, Chris McIntosh et autres

Representing NIH Genetic Test Registry Data in the FHIR Genomic Study Resource

Aly Khalifa, Robert R. Freimuth

The National Institute of Health (NIH) Genetic Testing Registry (GTR) provides a variety of information about genetic tests such as relevant methods, conditions, and performing laboratories. This study mapped a subset of GTR data to the newly developed HL7®-FHIR® Genomic Study resource. …

us (code pays fourni par la source)

Machine Learning Radiotherapy Automated Planning: Transition to an Ultra-hypofractionated Prostate Model

Vanessa Wan, Emily Ramchand, Aly Khalifa, Leigh Conroy et autres

ca (code pays fourni par la source)

The GA4GH Phenopacket schema defines a computable representation of clinical data

Julius O.B. Jacobsen, Michael Baudis, Gareth S Baynam, J. Beckmann et autres

gb, ch, au, es, us, ca, il, de, nl, fi, jp, sg, sa (code pays fourni par la source)

L2CS-Net: Fine-Grained Gaze Estimation in Unconstrained Environments

Ahmed A. Abdelrahman, Thorsten Hempel, Aly Khalifa, Ayoub K. Al-Hamadi

Human gaze is a crucial cue used in various applications such as human-robot interaction and virtual reality. Recently, convolution neural network (CNN) approaches have made notable progress in predicting gaze direction. However, estimating gaze in-the-wild is still a challenging problem due to …