• Advanced Institute of Engineering and Technology (AVITECH)

  • Seminars

    August 03, 2021: Dr. Andres Arias (Erasmus MC, Netherlands), MRI Imaging Biomarkers of Cancer

    Cancer disease is often difficult to get the right diagnosis and treatment. Gold standards to stage cancer and monitor disease progression are biopsy and imaging of tumor volume. However, the need for invasive biopsies to obtain the required tissue places limits on both spatial and temporal assaying of tumors. Also monitoring tumor volume progression limits earlier response in case the treatment is failing in certain patients. Therefore, effective biomarkers are needed for diagnosis, and predict and identify early response to treatment. Imaging biomarkers are especially useful because they are no-invasive, and allow high temporal and spatial sampling of tumors. In this presentation, I will show my work in how to identify predictive and early response MRI imaging biomarkers of two cancer treatments in early stage clinical trials.

    Speaker: Dr. Andres Arias, Erasmus MC

    Time: 15:30, Tuesday, August 03, 2021

    Venue: Webinar; Access code: https://bit.ly/3BKyptX

    speaker

    Dr. Andres Arias is an Electrical engineer, master in embedded system, and PhD in medical imaging. The focus of his PhD at Erasmus Medical Center was the combination of mathematics and computer science to develop medical imaging applications. From January 2018 he was a postdoc researcher working in medical imaging of cancer at Moffitt Cancer Center. Here, he has developed methods to identify imaging biomarkers to predict response to treatment in cancer patients using quantitative MRI. Dr. Andres Arias has (co-)authored nine peer reviewed publications and presented his work in several conferences.

    SAME CATEGORY

    February 2, 2024: Dr. Khoa D. Doan (Vin Univeristy) Toward Reliable and Practical Machine Learning Applications

    While Machine Learning (ML) has rapidly transformed several domains and applications with incredible successes, there are also important areas where the progress is significantly slower. Specifically, there exists a widened complexity gap between the methods currently investigated in research and those used in practice in these areas. One reason is that many algorithms, despite achieving […]

    February 2, 2024: Prof. Heng Ji (University of Illinois at Urbana-Champaign), Combating with Misinformation and Cancer: A Unified Multimodal AI Approach to Healthy and Happy Life

    A research overview of ongoing research projects, especially focusing on two that are most related to the VinUni-UIUC Smart Health Center: (1) Misinformation Detection and Trustworthy Large Language Models; (2) Joint Natural Language and Molecule Learning for Drug Discovery. Unsurprisingly these two seemingly different research problems can be tackled with a unified approach based on […]

    January 11, 2024: Dr. Le Duc Trong (FIT-UET) Resilient Multimodal Learning for Multimodal Emotion Recognition in the Presence of Incomplete Modalities

    Multimodal Emotion Recognition in Conversation (Multimodal ERC) is a critical area of research for interpreting human communication in diverse applications. Nevertheless, the persistent issue of uncertain missing modalities poses a major hurdle, hampering the development of robust Multimodal ERC models. Existing approaches face limitations in effectively leveraging a fusion of diverse data modalities encompassing audio, […]