Bio

My work involves designing and developing AI/ML-based algorithms to find answers for cutting-edge problems using multi-disciplinary data. This involves data from space-borne and ground-based instruments for astrophysics and space science studies, high-speed imaging data for behavioral neuroscience experiments, multi-omics data for finding biomarkers affecting population health, clinical data for detecting health anomalies, and EHR data for patient trajectory prediction and personalized medicine.

Contact

  • Academic
    tomin@stanford.edu
    University - Scholar Department: Anesthesiology, Perioperative and Pain Medicine Position: Postdoctoral Scholar

Additional Info

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All Publications

  • Comprehensive overview of the anesthesiology research landscape: A machine Learning Analysis of 737 NIH-funded anesthesiology primary Investigator's publication trends. Heliyon Ghanem, M., Espinosa, C., Chung, P., Reincke, M., Harrison, N., Phongpreecha, T., Shome, S., Saarunya, G., Berson, E., James, T., Xie, F., Shu, C. H., Hazra, D., Mataraso, S., Kim, Y., Seong, D., Chakraborty, D., Studer, M., Xue, L., Marić, I., Chang, A. L., Tjoa, E., Gaudillière, B., Tawfik, V. L., Mackey, S., Aghaeepour, N. 2024; 10 (7): e29050

    Abstract

    Anesthesiology plays a crucial role in perioperative care, critical care, and pain management, impacting patient experiences and clinical outcomes. However, our understanding of the anesthesiology research landscape is limited. Accordingly, we initiated a data-driven analysis through topic modeling to uncover research trends, enabling informed decision-making and fostering progress within the field.The easyPubMed R package was used to collect 32,300 PubMed abstracts spanning from 2000 to 2022. These abstracts were authored by 737 Anesthesiology Principal Investigators (PIs) who were recipients of National Institute of Health (NIH) funding from 2010 to 2022. Abstracts were preprocessed, vectorized, and analyzed with the state-of-the-art BERTopic algorithm to identify pillar topics and trending subtopics within anesthesiology research. Temporal trends were assessed using the Mann-Kendall test.The publishing journals with most abstracts in this dataset were Anesthesia & Analgesia 1133, Anesthesiology 992, and Pain 671. Eight pillar topics were identified and categorized as basic or clinical sciences based on a hierarchical clustering analysis. Amongst the pillar topics, "Cells & Proteomics" had both the highest annual and total number of abstracts. Interestingly, there was an overall upward trend for all topics spanning the years 2000-2022. However, when focusing on the period from 2015 to 2022, topics "Cells & Proteomics" and "Pulmonology" exhibit a downward trajectory. Additionally, various subtopics were identified, with notable increasing trends in "Aneurysms", "Covid 19 Pandemic", and "Artificial intelligence & Machine Learning".Our work offers a comprehensive analysis of the anesthesiology research landscape by providing insights into pillar topics, and trending subtopics. These findings contribute to a better understanding of anesthesiology research and can guide future directions.

    View details for DOI 10.1016/j.heliyon.2024.e29050

    View details for PubMedID 38623206

    View details for PubMedCentralID PMC11016610

  • Maternal vaccination to prevent adverse pregnancy outcomes: An underutilized molecular immunological intervention? Journal of molecular biology Giles, M. L., Sing Way, S., Marchant, A., Aghaepour, N., James, T., Schaltz-Buchholzer, F., Zazara, D., Arck, P., Kollmann, T. R. 2023: 168097

    Abstract

    Adverse pregnancy outcomes including maternal mortality, stillbirth, preterm birth, intrauterine growth restriction cause millions of deaths each year. More effective interventions are urgently needed. Maternal immunization could be one such intervention protecting the mother and newborn from infection through its pathogen-specific effects. However, many adverse pregnancy outcomes are not directly linked to the infectious pathogens targeted by existing maternal vaccines but rather are linked to pathological inflammation unfolding during pregnancy. The underlying pathogenesis driving such unfavourable outcomes have only partially been elucidated but appear to relate to altered immune regulation by innate as well as adaptive immune responses, ultimately leading to aberrant maternal immune activation. Maternal immunization, like all immunization, impacts the immune system beyond pathogen-specific immunity. This raises the possibility that maternal vaccination could potentially be utilised as a pathogen-agnostic immune modulatory intervention to redirect abnormal immune trajectories towards a more favourable phenotype providing pregnancy protection. In this review we describe the epidemiological evidence surrounding this hypothesis, along with the mechanistic plausibility and present a possible path forward to accelerate addressing the urgent need of adverse pregnancy outcomes.

    View details for DOI 10.1016/j.jmb.2023.168097

    View details for PubMedID 37080422

https://orcid.org/0000-0001-9010-7423