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Introduction
Biomedical image and signal processing for healthcare is experiencing tremendous growth worldwide, and biomedical jobs is one of the fastest growing career fields worldwide. This field is fundamental to the understanding, visualizing, and quantifying of medical images and bio signals in clinical applications. With the help of artificial intelligence and machine learning techniques, disease diagnosis will be easier, faster, and accurate leading to significant development in medicine in general. The goal of this course is to help learners develop basic skills in computational biomedical image and signal processing using the Python programming language and help them to appreciate the considerations in developing practical solutions for this domain.
- Graduate Certificate in Artificial Intelligence and AI Plus
- FlexiMasters in Artificial Intelligence and AI Plus
At the end of the course, learners are able to:
- Acquire basic knowledge on the fundamentals of biomedical image, signal processing and healthcare analysis
- Understand how to apply artificial intelligence and machine learning methods in a broad range of biomedical and clinical applications
- Hands-on coding in python mentored by Scientists for a small project on biomedical image, signal processing or healthcare data using various artificial intelligence or machine learning methods.
- Appreciation for considerations in deployment of practical AI and ML solutions for biomedical and clinical applications.
Scope:
AI for Biomedical imaging
- Overview of Biomedical imaging analysis
- AI for medical imaging, I/O, visualization, manipulation, and structure segmentation
- Deep learning for X-Ray and CT images
- Case: MRI Segmentation
AI for Biomedical Time Series and Healthcare Data Analysis
- Overview of Biomedical time series and healthcare data analysis
- Digital Frequency and Spatial Filtering
- Machine Learning and Classification
- Data Pre-processing and feature engineering
- Multivariate structured data processing
- Case: Signal processing on EEG data
- Case: Clinical Informatics: Predictive Analytics with Multimodal Data
- Case: Decision Support with EHR Data
Advanced Topics and Translational Considerations
- Semi-supervised learning
- Anomaly detection & Deployment considerations for AI innovations in healthcare
- Emerging research directions
- Frameworks for practical translation
No pre-requisites are needed to enrol in the individual courses.
Participants need to take note that those without qualifications or prior working experience in relevant engineering or the related fields, may find the course contents challenging.
Standard Course Fee: S$1,944
SSG Funding Support | Course fee payable after SSG funding, if eligible under various schemes | ||
Fee BEFORE funding & GST | Fee AFTER funding & 8% GST | ||
Singapore Citizens (SCs) and Permanent Residents (PRs) (Up to 70% funding) | s$1,800.00 | S$583.20 | |
Enhanced Training Support for SMEs (ETSS) | S$223.30 | ||
SCs aged ≥ 40 years old | |||
• NTU/NIE alumni may utilise their $1,600 Alumni Course Credits. Click here for more information.
Select one of the following options:
| COURSE TITLE | ACADEMIC UNIT |
| AI for Advance Manufacturing and Engineering | |
| CET870 AI for Advanced Manufacturing and Engineering (Basic) | 1 |
| CET871 AI for Advanced Manufacturing and Engineering (Intermediate) | 1 |
| CET872 AI for Advanced Manufacturing and Engineering (Advanced) | |
| AI for Bioimage, Signal Analysis & Healthcare | |
| CET874 AI for Bioimage, Signal Analysis & Healthcare (Intermediate) | 1 |
| CET875 AI for Bioimage, Signal Analysis & Healthcare (Advanced) | 1 |
| AI for Business Analytics | |
| CET876 AI for Business Analytics (Basic) | 1 |
| CET877 AI for Business Analytics (Intermediate) | 1 |
| CET878 AI for Business Analytics (Advanced) | 1 |
| AI for Drug discovery & Protein Interactions | |
| CET879 AI for Drug discovery & Protein Interactions (Basic) | 1 |
| CET880 AI for Drug discovery & Protein Interactions (Intermediate) | 1 |
| CET881 AI for Drug discovery & Protein Interactions (Advanced) | 1 |
| AI for Computational Geonomics | |
| CET882 AI for Computational Geonomics (Basic) | 1 |
| CET883 AI for Computational Geonomics (Intermediate) | 1 |
| CET884 AI for Computational Geonomics (Advanced) | 1 |
| AI for Accelerated Materials Development | |
| CET885 AI for Accelerated Materials Development (Basic) | 1 |
| CET886 AI for Accelerated Materials Development (Intermediate) | 1 |
| CET887 AI for Accelerated Materials Development (Advanced) | 1 |
| AI for Smart City and Urban Systems | |
| CET888 AI for Smart City and Urban Systems (Basic) | 1 |
| CET889 AI for Smart City and Urban Systems (Intermediate) | 1 |
| CET890 AI for Smart City and Urban Systems (Advanced) | 1 |
Listed courses are:
- Credit-bearing and stackable to Graduate Certificate in Artificial Intelligence and AI Plus (total 9AUs) and FlexiMasters in Artificial Intelligence and AI Plus (total 15AUs).
