--- 

hrs

---

AIHA8121 

Ethics are a set of moral principles that guide a person’s behaviour. In this course, ethics will be emphasized and considered the core value throughout all our daily and research activities. In addition, both the theoretical and the practical aspects of artificial intelligence (AI) empowered Smart Healthy Ageing will be introduced, including the fundamental methodologies and the state-of-the-art tools for healthcare. The topics also include data collection and proposal/paper writing. The course covers a wide range of key topics in modern AI-empowered Smart Healthy Ageing, from ethics to fundamental and professional research methodology.

3

45 hrs

---

AIHA8122 

Artificial Intelligence (AI) is becoming so pervasive that you may already be using it in your daily life. Machine learning is the science of making computers to learn without being explicitly programmed. Machine learning, including deep learning, is the manifestation of AI in the current era. In the past decade, machine learning has shown great achievements and even surpassed humans in many applications such as self-driving cars, speech recognition, machine translation, image recognition, etc. Due to its distinguishing advantages, machine learning has also been widely applied in biomedicine and healthcare, especially drug development, clinical diagnosis, response prediction, etc. This module covers some of the most important topics of machine learning. The aim of this module is to give students the theoretical underpinnings of AI and machine learning techniques, and to enable them to apply these methods to specific problems in biomedicine and healthcare with practice.

3

45 hrs

---

AIHA8299 

The doctoral thesis aims to allow students, by tackling advanced research problems over diverse settings, to significantly contribute to the expansion of knowledge in the field of AI-empowered Smart Healthy Ageing, especially in applied technology and produce a coherent body of work that is of scholarly value and worthy of publication. The work must be original and be the student’s own. There must be evidence that the field has been thoroughly surveyed by the student with critical exposition of relevant works, clearly demonstrating the mastery of a body of knowledge in the field and strong analytical skills. Students are responsible for ensuring that the thesis is presented in a clear, accessible and consistent format. Good project management practices and effective writing and oral presentation skills are essential to the successful completion of the thesis.

21

---

---

AIHA8123

This course introduces the principles and methodologies of evidence-based healthcare (EBH) and meta-analysis in healthcare research. Topics include systematic reviews, quantitative synthesis of evidence, evaluation of biases, statistical methods for combining data, and the use of meta-analysis in clinical decision-making. Emphasis will be placed on the critical appraisal of literature, the practical application of meta-analysis techniques, and the interpretation of results for evidence-based practice.

3

45 hrs

---

AIHA8124

Human posture and movement result from highly coordinated mechanical interactions between bones, joints, ligaments and muscles under the nervous system's control. Understanding the synthesis and control of human movement requires a complete knowledge of the force interactions within the neuromusculoskeletal system. The objectives of this course are to provide the mechanical basis underlying body posture and movement and to equip the students with the knowledge and techniques necessary for the analysis of human movement for clinical applications and research. Upon completion of this course, the students will be able to measure human movement using marker-based, image-based and 3D skeletal model-based data. A clear understanding of the AI-based methods for analysis of human posture and movement.

3

45 hrs

---