The 7th International Workshop on Deep Learning in Bioinformatics, Biomedicine, and Healthcare Informatics (DLB2H 2023)

in conjunction with

IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2023)

Description

In recent years, deep learning has been spotlighted as the most active research field with its great success in various machine learning communities, such as image analysis, speech recognition, and natural language processing, and now its promising potential is being actively discussed in the field of biomedicine. In particular, a dramatically increasing number of deep learning-based approaches have been proposed in biomedical images and signal processing. However, relatively little application of deep learning has been made in other biomedical areas such as genomics and computational biology due to the difficulty of definition and interpretation of deep learning architecture. Moreover, there are still many challenging tasks with many open problems in deep learning that need to be solved for active use in bioinformatics, biomedicine, and healthcare informatics.

The 7th International Workshop on Deep Learning in Bioinformatics, Biomedicine, and Healthcare Informatics (DLB2H) will be held in conjunction with IEEE International Conference on Bioinformatics and Biomedicine (BIBM) at Decenber 5 - 8, 2023. The goal of this workshop is to bring together researchers with expertise of deep learning in bioinformatics, biomedicine, and healthcare informatics and share current cutting-edge deep learning methodologies and its applications. Papers are welcome from the following topics (but not limited to):

  • Protein structures
  • Gene expression regulations
  • Genome-wide association studies
  • Protein function prediction
  • DNA-protein binding site identification
  • Clustering cancer subtypes
  • Single-cell clustering
  • Cancer diagnosis
  • 3D brain reconstruction (MRI/fMRI)
  • Tissue image classification/Organ segmentation
  • Anomaly detection
  • Human activity recognition
  • Human behavior monitoring

Important Dates (Tentative)

  • Full workshop paper submission due: October 10, 2023
  • Notification of paper acceptance: November 5, 2023
  • Camera-ready due of accepted papers: November 21, 2023
  • Workshop: December 5, 2023 (D1)
*D-Day

Paper Submission

Please submit a paper (4 page IEEE 2-column format, but can be up to 6 pages without an additionaly fee), via online BIBM paper submission system: https://wi-lab.com/cyberchair/2022/bibm22/scripts/submit.php?subarea=S21&undisplay_detail=1&wh=/cyberchair/2022/bibm22/scripts/ws_submit.php. Papers should be formatted to IEEE Proceedings Manuscript Formatting Guidelines. You can download the format instruction here: http://www.ieee.org/conferences_events/conferences/publishing/templates.html. Electronic submissions (in PDF or Postscript format) are required.

Submit a paper: Click here


Publication

All accepted papers will be published in the BIBM proceedings and IEEE Digital Library (Xplore).

Program

DLB2H, fully online workshop, will be held on December 5 (Istanbul time), 8am - 12pm. The program is here.

Online meeting

Presentations

  • MoTIF: a Method for Trustworthy Dynamic Multimodal Learning on Omics
  • Knee Joint Protection: Effect of Foot Pressure Position on Rectus Femoris EMG during Squats
  • ASD-GResTM: Deep Learning Framework for ASD classification using Gramian Angular Field
  • Cryptic binding site prediction with protein language models
  • Adaptive Multi-modal Data Fusion Method for Dermatosis Diagnosis
  • Adaptive Multi-modal Data Fusion Method for Dermatosis Diagnosis
  • DeepDualEPI: Predicting Promoter-Enhancer Interactions Based on DNA Sequence and Genomic Signals
  • A Factual Aware Two-Stage Model for Medical Dialogue Summarization
  • CTCM: Clustering based on three correlation matrices for multi-omics data integration and cancer subtype identification
  • Non-rigid Medical Image Registration Based on Unsupervised Self-driven Prior Fusion
  • MTr-Net:A multipath fusion network based on 2.5D for medical image segmentation

Program Chairs

  • Jung Hun Oh, Department of Medical Physics, Memorial Sloan Kettering Cancer Center, USA
    E-mail: ohj@mskcc.org
  • Kyungtae Kang, Department of Artificial Intelligence, Hanyang University, USA
    E-mail: ktkang@hanyang.ac.kr
  • Mingon Kang, Department of Computer Science, University of Nevada, Las Vegas, USA
    E-mail: mingon.kang@unlv.edu

Program Committee Members

  • Ananda Mondal, Florida International University
  • Ashis Kumer Biswas, University of Colorado Denver

Previous Workshops

  • 6th DLB2H in conjunction with IEEE BIBM 2022, Virtual
  • 5th DLB2H in conjunction with IEEE BIBM 2021, Virtual
  • 4th DLB2H in conjunction with IEEE BIBM 2020, Virtual
  • 3rd DLB2H in conjunction with IEEE BIBM 2019 in San Diego, CA, USA
  • 2nd DLB2H in conjunction with IEEE BIBM 2018 in Madrid, Spain
  • 1st DLB2H in conjunction with IEEE BIBM 2017 in Kansas City, MO, USA