BioMed Research International

The Emergence of AI Based Health Informatics

Publishing date
01 Mar 2023
Submission deadline
04 Nov 2022

Lead Editor

1Charles Darwin University, Casuarina, Australia

2University of Saskatchewan, Saskatoon, Canada

3Mawlana Bhashani Science and Technology University, Tangail, Bangladesh

This issue is now closed for submissions.

The Emergence of AI Based Health Informatics

This issue is now closed for submissions.


Recently, artificial intelligence and machine learning have been revolutionizing the landscape of healthcare research and personalized precision medicine. There are now great volumes of health data, including patient medical records that have been made available through wearable sensors, health insurance claims, medical imaging, surveillance, and more. With the increasing advancement in hardware components, the rapid progress of machine learning algorithms (primarily using deep learning methods to analyze clinical data) is gradually having the following effects: enabling doctors to better diagnose; facilitating early disease detection; uncovering novel treatments and drug interactions; improving disease surveillance; and others. The development and research in this field is progressing faster than ever before.

Deep learning has shown remarkable success in the field of health informatics. However, due to the complex structure of the model, it remains still a black box, and demystifying this black box has become a major challenge. Significant research is needed for such issues and to address the development of methods for improved interpretability of machine learning predictions, reducing brittleness, and improving generalizability.

The aim of this Special Issue is to collect a wide variety of research into machine learning based health informatics. Original research and review articles are welcomed.

Potential topics include but are not limited to the following:

  • Management of digital healthcare and health informatics innovations
  • Automated framework for disease diagnosis
  • Early disease diagnosis and relevant treatment prediction
  • AI-based pattern recognition methods
  • AI-based Data and security management for Wearable medical devices
  • Privacy and security in healthcare data management with A
  • Deep learning for medical image processing and decision making
  • Role and recent development of AI in Electronic Health Records
  • AI and its applications in bioinformatics and computational biology
  • AI-based cloud and data mining
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