Workshop Title:

Workshop on Machine Learning for Medicine 2023 (WMLM2023)


October 13th, 2023 (GMT+12)


Faculty of Medical and Health Sciences and Bioengineering Institute, The University of Auckland


  • Machine Learning
  • Artificial Intelligence
  • Biomedical Data Analysis
  • Medical Imaging
  • Image Guided Surgical Robot

Workshop Chair:

Dr. Alan Wang
Associate Professor in The University of Auckland

Personal Bio:

Alan Wang is a principal investigator and Associate Professor at The University of Auckland. He has more than ten years of research experience in bioengineering informatics and integrated medicine, especially in advancing the role of medical informatics in health care. His research interests include bioengineering, data informatics, neurocomputing, and biomedical statistics and simulation. He has developed medical data analytics methods for mobile health and personalized diagnosis and prognosis based on intelligent computing theories. He has experience analyzing huge cohorts of patient data with applications of early diagnosis, disease understanding, and effective treatment of patients with different disorders. He serves as an Editorial Board Member and an Active Reviewer for several international journals.

Workshop Description:


Machine learning (ML) has emerged as a transformative tool in the field of medicine. By leveraging vast amounts of patient data, ML algorithms can assist in disease diagnosis, risk prediction, and personalized treatment plans. In medical imaging, ML models analyze scans and images to enhance detection accuracy for conditions like cancer and cardiovascular diseases. Furthermore, machine learning expedites drug discovery by identifying potential candidates and optimizing formulations. Personalized medicine benefits from ML's ability to consider individual patient characteristics and provide tailored healthcare interventions. Electronic health records analysis enables the extraction of valuable insights, improving clinical decision-making and patient outcomes. Wearable devices and patient monitoring systems powered by ML algorithms offer real-time data analysis for early detection of health issues. With AI-powered chatbots and virtual assistants, patients can access medical information and preliminary diagnoses conveniently. Machine learning's integration with medicine holds immense promise for advancing healthcare delivery and improving patient care.


Workshop on Machine Learning for Medicine 2023 (WMLM2023) aims to bring together scientists, engineers, and students to discuss the latest advances in interdisciplinary research on machine learning for biomedical data analysis with clinical applications using machine learning and artificial intelligence techniques/methods. This workshop is designed to introduce Artificial Intelligence methods and connect them with applications that can leverage AI in research, such as cancer imaging quantitations, neurodegenerative diseases early diagnosis and prognosis, cardiovascular imaging quantifications and simulations, stroke prediction and rehabilitation, surgical navigation/robots, intelligent biosensors, etc.

Scope and Information for Participants:

Detailed research topics include, but are not limited to:

  • Artificial intelligence in medicine
  • Machine learning models for analyzing medical data
  • Image guided intervention
  • Image guided surgical robotics
  • Data mining in healthcare
  • Medical image analysis
  • Medical informatics
  • Intelligent medical diagnosis
  • Intelligent healthcare informatics
  • Biomedical knowledge
  • Biomedical knowledge reasoning, extraction, and graph construction
  • Explainable diagnostics support system
  • Multi-modal biomedical data analysis models
  • Multi-modal transformer models for biomedical data
  • Biomedical data anonymization
  • Privacy-aware biomedical data analysis and federated learning
  • Self-supervised learning for multi-modal biomedical data
  • Biomedical image/signal processing
  • Sensing, detection, and recognition in biomedical image/signal
  • Natural language processing and knowledge discovery in biomedical documents
  • Emerging digital healthcare applications
  • Mobile and cloud computing for digital healthcare
  • Security, trust, and privacy in digital healthcare


The Workshop on Machine Learning for Medicine 2023 offers a comprehensive exploration of the intersection between machine learning and the field of medicine. Join us on Friday, 13th October 2023, from 13:30 to 16:30 at Room 502-463, or connect remotely via Zoom. This workshop serves as a platform for experts, researchers, and practitioners to converge, exchange insights, and catalyze innovation in utilizing machine learning techniques to address critical medical challenges.

Throughout the workshop, participants will be immersed in the latest advancements and trends in machine learning tailored specifically to the realm of medicine. The presentations will cover various topics, ranging from cognitive training and neuromodulation in stroke, to cutting-edge applications like brain age estimation using T1-MRI. Attendees will gain profound insights into stroke lesion segmentation, deep learning methodologies, and quantification of multiple brain lesions. These presentations promise to illuminate the transformative potential of machine learning in the medical landscape.

The interactive nature of the workshop encourages dynamic discussions and meaningful exchanges among participants. By the conclusion of the event, attendees will emerge with a deeper understanding of how machine learning can revolutionize healthcare outcomes, diagnostics, and personalized medicine. Moreover, the Workshop on Machine Learning for Medicine 2023 provides a unique networking opportunity, fostering collaborations that have the potential to drive substantial progress in the dynamic field of machine learning in medicine.

Access to Workshop:

CONF-MLA 2023 Workshop -- Auckland - YouTube


Grafton Campus, The University of Auckland, Auckland 1023, New Zealand


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