American University of Beirut

Health & Life Sciences

​​​​This research theme spans different fields varying from the local, regional, to the global Public Health,  Life Sciences. and Medical Care.​

It covers data analysis of medical records through Image Processing as well as Natural Language Processing and the use of Computational Linguistics and Graph Theory applied, and not exclusively, to preprocess and annotate Arabic and medical documents. Additional examples in the analysis of datasets and image processing explore the associations of biomarkers and clinical outcomes for Risk Assessment, and the analysis of MRI for the identification of predictive markers in Multiple Sclerosis and other Neurological Diseases. 

This area also covers Health Informatics and Demographics such as the spatial distribution of the Arab region population, medical schools, and healthcare professionals. Health information and Road Traffic Injury (RTI) are also subject fields of this broad theme

Further, Maternal Health Improvement (GAIN MHI) is a focus area where Gamification and Artificial Intelligence for personalization are deployed through mobile applications to improve the quality of antenatal care services in Lebanon, in addition to the use of Machine Learning coupled to Wearable devices for healthy living. ​​

Below is a list of selected faculty members who conduct research relevant to this area

  • Arij Daou
    Computational Physiology with emphasis on computational neuroscience, Neural network modeling, and Dynamical Systems Analysis.
  • Catherine Schenck
    Exploring the contribution of spatial epidemiology and spatial data science to public health informatics and public health practice.
  • Fadi Zaraket
    Developing novel automated reasoning resources and techniques applied to problems in program correctness and language understanding.
  • Fatima Abu Salem
    A​dvanced machine learning techniques to model imbalanced datasets with a healthcare outcome.
  • Global Health Institute
    Applying data science to global health issues, including COVID-19.
  • Heinrich Dohna
    Computational biosciences and bioinformatics.
  • Hazem Hajj
    Machine Learning Models for Health including mental and phsyical health monitoring with wearable sensors and prediction models for 3D imaging such as CT scans and MRI.
  • Houry Puzantian
    Associations of biomarkers and clinical outcomes - including longitudinal analysis (survival and mixed effects modeling).
  • Khalid Yunis
    Using machine learning to improve health outcomes on a large dataset of 300,000 coupled mothers & newborns.
  • Mariette Awad
    Medical Record ( image and text) analysis, Wearables for healthy living.
  • Pierre Khoueiry
    Computational Genomics with emphasis on non-coding DNA and gene regulatory networks​.
  • Rouwaida Kanj
    Biomedical devices and sensor data analytics.
  • Saeed Raheel
    Integrating Quantum Computing with Machine Learning and Natural Language Processing, especially Arabic, to build more intelligent Agents that can be used in Medicine and Robotics​.
  • Salem Hannoun
    MRI/CT image assessment and processing (volumetry, atrophy, diffusion tensor imaging ...) through automatic and semiautomatic approaches.​
  • Samar Al-Hajj
    Health Analytics and visualization to assess, reduce and control Injuries.
  • Samer Kharroubi
    Bayesian modelling to evaluate the cost-effectiveness of health care interventions, Modelling preference-based health state utility data, measuring and valuing health and quality of life.​
  • Shadi Saleh
    Gamification, Artificial Intelligence, and mHealth Network for Maternal Health Improvement (GAIN MHI) [led by the Global Health Institute].  Exploring whether a Mobile Application that uses Artificial Intelligence for personalization will improve the quality of antenatal care services in Lebanon.
  • Shady Elbassuoni
    Deep learning for Medicine and Public Health​.

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