OIC-COMSTECH and Ningo University Certificate Course On Applied Biomedical AI
“Unlocking the Future of Healthcare & Life Sciences with Artificial Intelligence”
Guest Speaker
Prof. Dr. Yuzong Chen
Deputy Director, State Key Lab of Chemical Oncogenomic
Ningbo University, China
Technical Facilitator/ Speaker
Prof. Dr. Wang Likun
Ningbo University, China
Organized by:
Science, Technology and Innovation Center (STIC), COMSTECH
Workshop Details:
This certified course is designed for senior researchers, clinicians, data scientists, and academic faculty from the fields of Biotechnology, Bioinformatics, Computer Science, Pharmacy, and Life Sciences who are eager to integrate AI into biomedical applications. The program aims to equip participants with practical skills and hands-on experience in applying Artificial Intelligence to solve real-world challenges in healthcare and biomedical research especially in resource-constrained settings. Attendees will also gain insights into establishing and sustaining AI-driven biomedical research initiatives within their institutions.
Learning Objectives:
By the end of this course, the participants will:
- Understand the foundational principles and practical applications of AI in biomedicine and healthcare.
- Apply AI tools and techniques in data analysis, diagnostics, and research within resource-constrained environments.
- Identify their own training needs to enhance AI integration in biomedical and clinical research.
- Outline key requirements for establishing AI-powered biomedical research or clinical research centers in their institutions.
Target Audience:
- Senior Healthcare Professionals and Researchers
- Faculty Members and Academic Leaders in Life Sciences, Computer Science, and Biomedical Fields
- Healthcare Administrators and Policy Makers
- Government Officials involved in S&T, Health, and Education sectors
- Data Scientists and AI Enthusiasts working in biomedical research
Course Module:
| Lecture No. | Title | Topics Covered |
| 1 | AI Overview | What is AI? How does AI work? Machine learning vs. deep learning, history of AI |
| 2 | AI and Big Data in Biomedicine | AI and big data in language, image, audio, biomedicine; biomedical databases |
| 3 | Supervised Machine Learning Methods – Part 1 | Simple supervised ML methods, k-nearest neighbor, Bayesian classifiers |
| 4 | Supervised Machine Learning Methods – Part 2 | SVM, decision trees, random forest, performance measurement, training with small datasets |
| 5 | Unsupervised Machine Learning Methods | Distance/similarity measures, hierarchical clustering, K-means, fuzzy C-means |
| 6 | Machine Learning Regression Methods | Linear/polynomial regression, PCA, PLS, logistic regression, ridge, LASSO |
| 7 | Biomedical Machine Learning | Applications of ML in biomedical fields |
| 8 | Data Dimensionality Reduction, Feature Selection & Biomedical Applications | PCA, t-SNE, UMAP, visualization, feature selection methods, biomedical applications |
| 9 | Deep Learning CNN Models | Basics of Convolutional Neural Networks (CNNs) |
| 10 | Deep Learning Biomedical CNN Models | CNNs applied to biomedical data and diagnostics |
| 11 | Word Embedding and Bio molecular Encoding | Word embedding techniques, biomolecule encoding (DNA, RNA, protein), chemical and food encoding |
| 12 | Recurrent Neural Network (RNN) and Applications | RNN basics, LSTM, RNN vs. LSTM, applications in sequence data |
| 13 | Transformer | Attention mechanisms, introduction to Transformer architecture |
| 14 | Pharmaceutical Deep Learning Models | Drug discovery, deep learning in pharmaceutical applications |
| 15 | Spectroscopic Deep Learning in Biochemistry & Biomedicine | Spectroscopy techniques, DL models for spectroscopic data |
| 16 | Metabolomic ML and DL | Metabolomics, ML and DL applications in metabolomics |
| 17 | Microbial Genomics & Metagenomic Deep Learning | Microbial genomics, metagenomics, deep learning applications |
| 18 | Herbal AI | Traditional medicine, herbal databases |
| 19 | Food Machine Learning and Deep Learning | Food tech, databases, ML and DL in food science |
- Poster of Certified Course: Attached
- Date: 23rd – 31st July-2025
Session 2: 11th August – 15th August 2025 (Excluding 14th August 2025; Public holiday in Pakistan)
Session 3: 18th – 22nd August 2025
Session 4: 25th – 27th August 2025
- Timing: 1:30PM (Pakistan Standard Time)
- Procedure to join: In-Person- Online
- Registration link: Click Here
- Address: COMSTECH Secretariat, 33-Constitution Avenue, G-5/2, Islamabad
Phone No. : 92 51 9220681-3
Email: comstech@comstech.org