Introduction to AI Applications in Pulmonary Medicine
- Offered byFutureLearn
Introduction to AI Applications in Pulmonary Medicine at FutureLearn Overview
Introduction to AI Applications in Pulmonary Medicine
at FutureLearn
Duration | 4 weeks |
Total fee | ₹2,763 |
Mode of learning | Online |
Credential | Certificate |
Introduction to AI Applications in Pulmonary Medicine at FutureLearn Highlights
Introduction to AI Applications in Pulmonary Medicine
at FutureLearn
- Earn a certificate upon completion
Introduction to AI Applications in Pulmonary Medicine at FutureLearn Course details
Introduction to AI Applications in Pulmonary Medicine
at FutureLearn
More about this course
- On this four-week course from Taipei Medical University, you’ll explore the applications of AI in the diagnosis, clinical management, and research of respiratory diseases
- You’ll be introduced to medical ethics and examine the ethical issues that surround AI applications, giving you a deeper, contextualised knowledge of AI treatments and usage
- Gaining insights into cutting edge technology, you’ll be able to identify the advantages and limitations of different AI technology when diagnosing and classifying diseases
- You’ll learn how innovative technology can help detect changes in sleep disordered breathing, diagnose sleep apnea conditions, and analyse the severity and type of disease
- You’ll also discover how the data collected can be synthesised and used to develop treatment methods
Introduction to AI Applications in Pulmonary Medicine at FutureLearn Curriculum
Introduction to AI Applications in Pulmonary Medicine
at FutureLearn
AI in respiratory medicine: current trends and future possibilities
Macine learning and deep learning in pulmonary diagnosis
AI in Pulmonary Medicine: Ethics of Artificial Intelligence
The role of AI in diagnosing lung diseases
The application of AI in image research and deep learning
Lung lesions detection software
AI and IoTs for sleep disordered breathing and post Covid-19 respiratory care
Techniques for identifying and classifying sleep breathing disorders
Improvements in data analytics and care platforms
AI for home-based pulmonary rehabilitation in COPD
Smart telemedicine for chronic obstructive pulmonary disease
Home based rehabilitation for COPD
Assessment and course feedback
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