41882-Jo, Taeho

Taeho Jo, PhD

Assistant Research Professor of Radiology & Imaging Sciences

Email tjo@iu.edu
355 W. 16th Street, GH 4093

Indianapolis, IN 46202


Dr. Taeho Jo has over a decade of experience in biochemistry, biophysics, neuroscience informatics, and deep learning. After obtaining his Ph.D. in Computational Biology from Tokyo Medical and Dental University in 2010, he joined the Indiana Alzheimer's Disease Research Center and the Indiana University Center for Neuroimaging in 2018. Here, he applied AI techniques to Alzheimer's disease research, resulting in a publication titled "Deep Learning in Alzheimer's Disease: Diagnostic Classification and Prognostic Prediction Using Neuroimaging Data" in Frontiers in Aging Neuroscience 2019 (PMID: 31481890). This was followed by his work on a 3D convolutional neural network (CNN) classification model for tau positron emission tomography (PET) scans, published in BMC Bioinformatics 2020 (PMID: 33371874), achieving a classification accuracy of 90.8% for Alzheimer's disease in cognitively normal subjects . Further expanding on his genomics research, Dr. Jo introduced the Sliding Window Association Test (SWAT) CNN method, published in Briefings in Bioinformatics 2022 (PMID: 35183061), and the Circling Sliding Window Association Test (c-SWAT) for lipidome-based Alzheimer's disease analysis in eBioMedicine 2023 (PMID: 37806288). His efforts were funded by the Alzheimer's Association for the project "A Dual-Deep Learning AI Strategy to Identify Tau-associated Genetic Variants in Alzheimer's Disease", and tools such as SWAT-Web, along with codes for SWAT, c-SWAT, and other related projects, have been open-sourced on GitHub.

Key Publications

Taeho Jo, Junpyo Kim, Paula Bice, Kevin Huynh, Tingting Wang, Matthias Arnold, Peter J. Meikle, Rima Kaddurah-Daouk, Andrew J. Saykin*, and Kwangsik Nho*, “Circular-SWAT for deep learning based diagnostic classification of Alzheimer’s disease: Application to metabolome data”, eBioMedicine (2023)
Taeho Jo,
Kwangsik Nho*, Paula Bice, and Andrew J. Saykin*. "Deep learning-based identification of genetic variants: Application to Alzheimer’s disease classification." Briefings in Bioinformatics (2022)
Taeho Jo, Kwangsik Nho, Shannon L. Risacher, and Andrew J. Saykin*. "Deep Learning Detection of Informative Features in Tau PET for Alzheimer’s Disease Classification." BMC Bioinformatics (2020)
Taeho Jo*, Kwangsik Nho, and Andrew J. Saykin. "Deep Learning in Alzheimer's disease: Diagnostic Classification and Prognostic Prediction using Neuroimaging Data." Frontiers in Aging Neuroscience (2019) 11:220.

Titles & Appointments

  • Assistant Research Professor of Radiology & Imaging Sciences
  • Education
    2010 PhD Tokyo Medical and Dental University
    2002 BA Inha University
  • Research
    Alzheimer's Disease (AD) is intricately linked with abnormal tau protein accumulation. One of the crucial tasks in AD research is the identification of single nucleotide polymorphisms (SNPs) and associated metabolomics data, as these provide a deeper understanding of the disease's pathogenesis. Dr. Taeho Jo has been striving to devise an innovative deep learning strategy that integrates neuroimaging, genetic data, and metabolomic information, intending to build a more comprehensive understanding of AD.

    Methodological Workflow of the SWAT-ensemble Deep Learning Model
  • Professional Organizations
    Alzheimer's Association
    International Society for Computational Biology

Looking for patient care?

To schedule an appointment with a faculty member physician of IU School of Medicine, contact Indiana University Health at 888-484-3258 or use the physician finder by clicking the button below.

Find a doctor