This workshop will empower healthcare professionals with the knowledge and skills to leverage artificial intelligence (AI) in their practice. It aims to bridge the gap between cutting-edge technology and everyday clinical, research, and educational practice. The platforms covered in the workshop include Elicit.org, Scholarcy.com, Typeset.io, ChatGPT, Botpress.com, InVideo.io, and Genie.io.
The objectives of this specialised workshop are to:
• Explore the core principles of AI, emphasising its applications and significance in modern healthcare.
• Examine the role of AI in enhancing clinical judgment and patient management, with live demonstrations of relevant tools.
• Uncover the potential of AI in revolutionising teaching and learning experiences for healthcare professionals and students.
• Illustrate the integration of AI in healthcare research, focusing on tasks such as literature review, data analytics, and manuscript development.
• Provide a hands-on experience with various AI platforms tailored to healthcare professionals' unique needs and demands
1. AI in Healthcare
Vaikunthan Rajaratnam
Senior Consultant Hand Surgeon, KTPH, Singapore,
Adjunct Professor & UNESCO Chair Partner,
Asia Pacific University of Technology and Innovation, Malaysia.
25 November 2023
2. Warning:
Unprecedented Levels of Productivity
and Inspiration Ahead!
Please be advised:
The content of this workshop is so intensely
engaging and empowering in the realm of AI in
healthcare that it carries a high risk of sparking a
newfound addiction to productivity and innovation.
Attendees may experience an irresistible urge to
apply transformative skills and insights in their
professional practice, leading to significant
advancements in healthcare. Proceed with
enthusiasm and caution – you're stepping into a
world of exhilarating empowerment!
Embrace the journey, but don't say we didn't
warn you!
3. Disclaimer
• I am not an AI expert, nor do I possess coding knowledge specific to the underlying mechanisms of AI models;
• My expertise lies in the utilisation of these models, such as ChatGPT, based on my extensive experience as a
user within the fields of healthcare, medical education, and related research, rather than their technical
development or underlying algorithms.
• This workshop is intended solely for educational and informational purposes in AI and healthcare.
• The views expressed herein are my own, borne from extensive experience in surgery, medical education, and
instructional design, and do not necessarily reflect those of any associated institutions.
• While I endeavour to provide accurate and up-to-date information, no guarantee is given regarding its applicability.
• Participants acknowledge and assume responsibility for using the information provided by engaging in this
workshop.
Vaikunthan Rajaratnam
6. Framework for the Integration of Generative AI Skills into the
Teaching and Learning Practice
Domains
Foundational Knowledge of
AI and Generative AI
Pedagogical
Integration
Technical Proficiency
Ethical and Responsible
Use
Assessment and Evaluation
Professional Development
and Lifelong Learnin
Community and
Stakeholder Engagement
Rubrics
Understanding AI Concepts,
Fundamentals of Generative AI
Descriptors
Grasp of basic AI terminologies and principles; Demonstrates the
capabilities and limitations of generative models.
Curricular Mapping, Instructional
Design
Demonstrates the ability to align Generative AI tools with
curricular goals; Proficiency in integrating Generative AI in lesson
designs.
Tool Management, Data Literacy Skill in selecting and operating Generative AI platforms;
Demonstrates the ability to interpret and analyse data.
Data Privacy, Ethical Considerations Demonstrate the incorporation and compliance with data
protection laws in the practice; and the ethical implications,
including biases.
Formative Assessment, Summative
Evaluation
Demonstrate the capability to employ Generative AI for real-time
assessments; Integrate using AI data for evaluations.
Self-updating, Peer Training Demonstrate commitment to staying updated with AI
advancements; Willingness to train and mentor peers..
Communication, Collaboration Demonstrate the ability to articulate the role of Generative AI to
stakeholders; Actively seeking partnerships with experts.
7. Section Ethical Principles or Elements Description
Beneficence and Non-
Maleficence
Holistic Well-being Beyond intellectual growth, AI should contribute to emotional and social well-being.
Cultural Relevance Educational content should respect and incorporate local traditions, beliefs, and moral
systems.
Autonomy Informed Participation Users should be fully informed about how AI will be used.
Agency Family and community should also be involved in decision-making processes regarding
AI adoption in education.
Social Justice Equitable Access Special focus on providing equal access to quality education across various societal
strata.
Bias Mitigation Efforts must be made to eliminate biases related to gender, social class, or ethnicity.
ASIAN Values Harmony AI should aim for social harmony and integrate well with existing educational systems.
Respect for Authority AI should not undermine the teacher's role but should enhance the traditional teacher-
student relationship.
Stakeholder Collaboration Government Agencies Develop and enforce regulations and guidelines.
Educational Institutions Implement and adhere to ethical guidelines.
AI Developers Ensure the ethical design and deployment of AI.
Ethicists and Philosophers Continually review and update ethical guidelines.
Community and Family Participate in decision-making processes.
Evaluation and Monitoring Regular Audits Conduct regular ethical audits to ensure that AI tools comply with the framework.
Feedback Loops Create mechanisms for students, educators, and families to provide feedback on AI
ethical considerations.
8. PRODUCTS
• Tools for Effective Academic Courses and Holistic Teaching
•MOE Malaysia
AI TEACH
• Learning Designs
•APU, Malaysia, NHG, Singapore
AI LD
• Health Professional
•Perdana University , Malaysia, BDSSH, Bangladesh
•NHG, Singapore, Sengkang, Singapore
AI HP
• Research
•Perdana University, Malaysia, Sengkang , Singapore
•University of Eswatini (Africa)
AI RE
•Academic Writing
•APU, Perdana University, Malaysia
•University of Eswatini (Africa)
AI AW
• Leveraging Efficiency in Administrative Proficiency
•MOE, Dubai
AI LEAP
9.
10. Introduction to AI in
Healthcare:
Opportunities and
Challenges
AI technologies have the potential to
revolutionise healthcare by enhancing
diagnosis, treatment planning, and research.
AI won't replace you, but someone
empowered by AI undoubtedly will
11.
12. Secinaro, S., Calandra, D., Secinaro, A., Muthurangu, V., & Biancone, P. (2021). The role of artificial intelligence in healthcare: A structured
literature review. BMC Medical Informatics and Decision Making, 21(1), 125. https://doi.org/10.1186/s12911-021-01488-9
14. Predictiv
e
medicine
Early Disease Detection
Personalized Treatment Plans
Chronic Disease Management
Genomic Medicine and Genetic Risk Prediction
Drug Response Prediction
Epidemic Outbreak Prediction
Hospital Readmission Prediction
17. Challenges
Golhar, S. P., & Kekapure, S. S. (2022). Artificial Intelligence in Healthcare—A Review. International Journal of Scientific
Research in Science and Technology, 9(4), 381–387. https://doi.org/10.32628/IJSRST229454
18. Governance
Model for AI
S. Reddy, S. Allan, S. Coghlan, and P. Cooper, ‘A governance model for the application of AI in health care’, J. Am. Med. Inform. Assoc., vol. 27, no.
3, pp. 491–497, Mar. 2020, doi: 10.1093/jamia/ocz192
Rahman, N., Thamotharampillai, T., & Rajaratnam, V. (2023). Ethics, guidelines, and policy for technology in healthcare. In
Medical Equipment Engineering: Design, Manufacture and Applications (pp. 119–147). IET Digital Library.
https://doi.org/10.1049/PBHE054E_ch9
19. Higgins, D., & Madai, V. I. (2020). From Bit to
Bedside: A Practical Framework for Artificial
Intelligence Product Development in
Healthcare. Advanced Intelligent Systems,
2(10), 2000052.
https://doi.org/10.1002/aisy.202000052
20. EPIC and AI
Abridge's Clinical
Documentation
Tool Integration:
• Creates near-instant
visit summaries.
Generative AI for
Patient Messaging
by Ochsner Health:
• Generative AI to draft
messages to patients.
Partnership with
Microsoft
• Integrate large
language models
Emory Healthcare's
Collaboration with
Abridge:
• Ambient listening
solution for note-taking
during doctor's
appointments.
21. Personalised chatbots & Epic EHR system
• Interprets caller intent and provides
immediate, personalised assistance
Avaamo's AI-Powered
Patient Experience:
• Automates patient communications.
Asparia's Chatbot
Integration:
• Extract and analyse patient data &
generates detailed medical reports
Epic-Chatbot Using
ChatGPT
22. Artificial
Intelligence
Enables machines
to mimic human
intelligence and
perform tasks that
typically require
human intelligence
• Machines learn from data
• recognize patterns
• make decisions, and
• solve problems without explicit
programming
• Algorithms and statistical models
• analyse large amounts of data
• generate insights and predictions.
• Narrow AI
• designed for specific tasks like image
recognition or natural language
processing, and
• General AI
• aims to possess human-like intelligence
across a wide range of tasks.
24. What is Generative AI?
• Understanding Language
• Reads and comprehends human-written text.
• Generating Text
• Writes human-like text, from answers to creative content.
• Conversation
• Capable of engaging in text-based conversations with users.
• Applications
• Used in virtual assistants, education, content creation, and
more.
• Not a Human
• Generates text through algorithms, without feelings or
consciousness.
AI for Clinical Decision-Making and Patient Care
25. AI & Generative AI
• AI (Artificial Intelligence)
• refers to the simulation of human intelligence in
machines that are programmed to think, learn, and
make decisions
• Applications: Includes machine learning, natural
language processing, robotics, computer vision, etc.
• Generative AI
• subset of AI that focuses on creating new data
instances that are similar to a set of training
examples.
• Techniques: Examples include Generative Adversarial
Networks (GANs), Variational Autoencoders (VAEs),
etc.
• ChatGPT (Generative Pretrained Transformer):
• State-of-the-art language models developed by
OpenAI. It utilises the Transformer architecture to
generate human-like text based on given prompts.
• Usage: Widely used in natural language understanding
tasks, chatbots, content creation, and more.
• Bing CoPilot
• Bard
• Claude 2
26. How Does Generative AI Work?
Don’t cry ………..”
“ Don’t cry over….”
• Reading Text
• Takes in words, questions, or
sentences as input
• Understands the language like a
human reading a book
• Processing Information
• Breaks down the input into
smaller parts to understand the
meaning.
• Uses a complex mathematical
model to analyse the text.
• Generating Response
• Constructs a response based on
what it has "learned" from
reading lots of text.
• Tries to make the response sound
like something a human would
say.
• No Personal Knowledge or Opinions
• Doesn't have thoughts, feelings,
or personal experiences.
• Answers are based on patterns in
the data it was trained on, not
personal beliefs or opinions.
• Learning from Data
• Trained on vast text from
books, websites, and other
written materials.
• Learns language structure
and how to create sentences
that make sense.
• Versatility
• Can be used for tasks like
answering questions, writing
stories, or helping
with homework.
• Adaptable to different
subjects and contexts.
• Not Perfect
• Can make mistakes or provide
incorrect information.
• Needs to be used with
caution, especially for critical
or sensitive topics
28. Understanding Generative AI
• Advanced language
model developed by
OpenAI.
• Generates human-like
text based on the
prompts.
• Quality vs prompt.
Quality of Response ∝ Quality of Prompt × Model Understanding
Here:
Quality of Response is the measure of how relevant, accurate, and coherent the response is.
Quality of Prompt represents the clarity, specificity, and relevance of the prompt given to the model.
Model Understanding , model's ability to interpret the prompt, including its training, design, and current context.
30. Tool: Prompting
"prompting" refers to the input or
question that you provide to the
model. The model takes this prompt
and generates a response based on
the information it has been trained
on.
• Initial Statement or Question
• Context
• Intended Output
• Tone or Formality
• Specificity
• Instructions for Response Format
31. Prompt Generation
• Define the Objective:
• Identify the specific information or assistance
• Be Clear and Precise:
• Use clear language and avoid ambiguity.
• Include essential details without over-
complicating the prompt.
• Consider Context:
• Provide relevant background or context to
guide the response.
• Set the Tone and Style:
• Specify the desired tone (formal, casual) or
style (e.g., summary, explanation) if it matters
for your use case.
• Ask Direct Questions:
• If seeking specific information, formulate your
prompt as a direct question.
• Self-Reflective
• Avoid Bias and Leading Questions:
• Craft the prompt neutrally to prevent biased
or skewed responses.
• Test and Refine:
• Experiment with different phrasings and
observe how slight changes can affect
the response.
• Refine the prompt
• Consider Ethical and Privacy Concerns:
• Ethical guidelines and does not request or
reveal sensitive or private information.
32. Bad Prompts Comments Good Prompts Comments
Tell me about heart
problems.
Too vague, lacks
focus and context.
Summarize the diagnostic criteria for
Congestive Heart Failure according to
the latest ACC/AHA guidelines.
Specific, focused, and
references a reputable
source.
What drugs are good
for high BP, diabetes,
and heart issues?
Overly complex,
risks dangerous
oversimplification.
List the first-line antihypertensive
medications according to the latest
guidelines.
Focused on a single
condition, asks for
evidence-based
treatment.
What's the best
treatment for a 45-
year-old male named
John Smith with
these symptoms?
Contains potentially
identifiable
information, risking
patient
confidentiality.
What are the treatment options for a
45-year-old male presenting with
these generic symptoms?
Generalized and
anonymized,
preserving patient
confidentiality.
33. Response Validation
• Review response - meets your requirements.
• No access to real-time data
• Vaildate Validate Validate.
• Prompt – response -refine - reprompt.
Relevance Check
Accuracy
Confirmation
Context
Consistency
Sensitivity Review
Refinement for
Future Queries
36. Please respond to the following query with a
structured and academic approach suitable for
a university lecturer.
Include bullet-point answers where applicable,
supported by relevant examples from scholarly
literature.
Ensure that all statements are backed by
credible evidence and provide appropriate
references and citations in accordance with
standard academic citation styles (e.g., APA,
MLA, or Chicago).
The response should be clear, concise, and
tailored to an academic audience engaged in
higher education teaching and research."
Personalizing Gen-AI
37. • Professional Tone & Evidence-Based Approach: Maintain a formal tone and
rely on evidence-based information, aligning with Dr. Rajaratnam's scholarly
background.
• Expertise in Healthcare, Education, and AI: Prepare for in-depth discussions
in these fields, reflecting Dr. Rajaratnam's extensive experience and
contributions.
• Ethical and Global Perspective: Factor in ethical considerations for AI
applications and be sensitive to international norms, given Dr. Rajaratnam's
global collaborations and ethical guidelines.
• Technological and Interdisciplinary Focus: Be ready to introduce tech-based
solutions and consider interdisciplinary approaches, corresponding with his
interests in instructional design and AI.
• Social Impact and Local Context: Prioritize broader social impact and
humanitarian goals, and adapt information to the Singaporean and Malaysian
context, where Dr. Rajaratnam is actively engaged.
38.
39. Generative
AI platforms
Feature ChatGPT Microsoft Copilot
Integration
Available as an API that can
be integrated into different
applications1
Integrated with Microsoft
365 and other services1
Specialization
Designed to mimic human
conversation by
understanding your question
or comment and responding
in an engaging and
conversational way1
AI-powered digital assistant
that aims to provide
personalized assistance to
users for a range of tasks and
activities1
Versatility
Can handle a wide range of
tasks and domains, such as
writing essays, emails,
poems, songs, summaries,
etc1
Combines the power of large
language models (LLMs) with
your data in the Microsoft
Graph (including your
calendar, emails, chats,
documents, meetings, and
more) and the Microsoft 365
apps1
Control
Gives more control to the
user over what they want to
generate1
Works as a digital assistant
that fills in the blanks for the
user1
40.
41.
42. Aspect ChatGPT Response Other Chatbot Response
Non-invasiveness & Practicality Mentioned as a key advantage,
emphasizing suitability for
community settings.
Highlighted as a practical tool for
community screening due to its
rapid, non-invasive nature.
Early Detection Stressed the ability to detect
small fiber damage before clinical
symptoms.
Noted for its use in early
detection, particularly of small
fiber nerves.
Correlation with Neuropathy
Severity
Discussed the correlation
between CCM findings and
neuropathy severity.
Not specifically addressed.
Predictive Value Mentioned its potential in
predicting the development of
diabetic neuropathy.
Focused on predictive validity,
especially for future development
of Diabetic Peripheral
Neuropathy.
Repeatability and Reliability Emphasized the importance of
repeatability and reliability.
Briefly mentioned as repeatable
but didn't elaborate on reliability.
Telemedicine Potential Addressed the potential use in
telemedicine.
Not discussed.
Limitations and Challenges Discussed limitations such as the
need for specialized equipment
and training.
Not discussed.
Detailed Description Provided a detailed, multifaceted
analysis.
More focused on key points, less
detailed in comparison.
43. ChatGPT4 Opinion
• ChatGPT Response: This response is comprehensive,
addressing various aspects, including predictive value,
telemedicine potential, and limitations. It provides a nuanced
understanding of CCM's role in diabetic neuropathy screening,
suitable for an audience seeking an in-depth analysis.
• Co Pilot Response: This response is concise and focused,
highlighting key advantages of CCM, such as its non-
invasiveness and predictive validity. It's more streamlined,
making it suitable for readers looking for a quick overview
without extensive background detail.
ChatGPT offers a detailed, academic-oriented approach, beneficial for in-depth understanding, while the other chatbot provides
a succinct summary, ideal for a general overview. Both have their unique strengths, and the preference would depend on the
depth of information and type of analysis the user requires.
44. Copilot Opinion Copilot Response GPT4 Response
Early Detection
Emphasized the ability of CCM to detect
small fibre damage at an early stage.
Highlighted the importance of early
detection and intervention in diabetes.
Non-Invasive Nature
Mentioned the non-invasive nature of
CCM.
Discussed the non-invasive nature of
CCM and its suitability for community
settings.
Predictive Value
Highlighted the predictive value of CCM
in identifying high-risk individuals.
Discussed the predictive capability of
CCM in identifying high-risk individuals.
Repeatability and
Reliability
Discussed the repeatability and reliability
of CCM for monitoring disease
progression.
Mentioned the repeatability and
reliability of CCM, and its importance for
longitudinal studies and screening
programs.
Correlation with
Neuropathy Severity
-
Mentioned the correlation of CCM
findings with neuropathy severity.
Potential in
Telemedicine
-
Discussed the potential of CCM in
telemedicine.
Limitations and
Challenges
-
Outlined the limitations and challenges
of implementing CCM in community
settings.
Please note that “-” indicates that the topic was not
covered in the respective response.
Both responses provide
a comprehensive
overview of the role of
CCM in diabetic
neuropathy screening.
However, the user’s
response provides a
more detailed
discussion by including
the correlation with
neuropathy severity,
potential in
telemedicine, and the
limitations and
challenges of CCM.
These additional details
offer a more nuanced
understanding of the
practical implications
of using CCM in
community settings
45.
46. Login to your choice of
Generative AI
• Ask a clinical question based on a good
prompt and have three conversations
related to your question.
• Share your responses
• How would you use it in your practice?
• Post to this Padlet
48. Patient Triage:
•Appropriate level of
care
Mental Health
Support:
•Immediate, cost-
effective
Patient
Education:
•Provide reliable and
continuous
information, explain
treatment options, or
clarify post-operative
care instructions.
Remote
Monitoring:
•Ensure medication
adherence, and alert
clinicians about
anomalies.
Clinical Decision
Support:
•Data-driven insights
to support clinical
decisions.
Confidentiality and
Compliance:
Ensure that all interactions are
secure and compliant with
healthcare regulations.
68. Use a clinical situation / administrative problem and
craft prompts for the various AI platforms
and post the response
69. Relevance to healthcare education
• Adapts to individual student needs
Personalized
Learning:
• Creating diverse and engaging educational materials.
Content Creation:
• Interactive learning experiences (Chatbot)
Student Engagement:
• Provides real-time assessment and feedback .
Assessment and
Feedback:
• content accessible to diverse learners
Accessibility:
• Facilitates collaboration among students and educators,
bridging geographical and language barriers.
Collaboration and
Communication:
70. Personalized Learning
• Tailors educational content
Adaptive Content Delivery:
• Provides instant feedback and real-time assistance
Real-Time Feedback and
Support:
• Engages with interactive dialogues and Simulates scenarios.
Interactive Learning
Environments:
• Analyses - identify strengths and weaknesses for personalized learning.
Data-Driven Insights:
• Adapts content to diverse learners & multiple languages.
Accessibility and Inclusivity:
• Facilitates collaborative learning experiences and peer interactions.
Collaboration and Peer
Interaction:
• Seamlessly integrates with Learning Management Systems (LMS)
Integration with Existing
Platforms:
• Supports lifelong learning and Assists in tracking and maintaining
professional development
Continuous Learning and Skill
Development:
• Ensures ethical guidelines and privacy regulations.
Ethical and Privacy
Considerations:
• Aligns personalized learning experiences and Ensures relevance to real-
world medical practice
Alignment with Healthcare
Objectives:
75. 1.Question: Which of the following statements best describes
the role of HbA1c in managing diabetes?
1. A) HbA1c is primarily used to diagnose acute diabetic
complications.
2. B) HbA1c levels reflect the average blood glucose levels
over the past 2-3 months.
3. C) HbA1c is a short-term marker for blood glucose
fluctuation.
4. D) HbA1c measures the immediate postprandial blood
glucose level.
Answer: B) HbA1c levels reflect the average blood glucose
levels over the past 2-3 months.
1.Question: A 54-year-old patient with Type 2 diabetes presents
with an HbA1c of 8.0%. What is the most appropriate initial
approach?
1. A) Immediate hospitalisation for insulin therapy.
2. B) Evaluation and optimisation of the current treatment
regimen.
3. C) Disregarding the HbA1c level as it is within the normal
range.
4. D) Starting an antihypertensive medication
.hospitalisation
78. I have been asked
to create a module
for the
examination of the
abdomen for
organomegaly for
medical students.
Create a
curriculum and
include learning
outcomes and the
pedagogy and a
lesson plan
88. • Be clear & descriptive
• Specific styles or
techniques
• Create a test version
• Evaluate the result
• Refine the prompt
• Iterative process
89. AI for Video Production & Image
generation
Draft
Learning
Outcomes
LO to
Prompt
ChatGPT
for video
script
Import/edi
t script to
AI Video
Generator
Add
personalised
media
Choose
Voiceover
type
Produce
Review
and
Upload
90. Write a script
for the
introduction of
the anatomy of
the
organomegaly
medical student
module. This
will be a 90
second video
script. Just
provide the
narration
98. Generating Lecture
Content
• Participants use
their prompts to
generate an outline
and main content
for a lecture.
Validating AI
Responses
• Participants validate
and refine the AI-
generated content
for their lecture.
Integrating and
Refining Lecture
Content
• Finalizing the
lecture content,
incorporating
validated
information and
personal expertise.
99. Part 1: Scriptwriting
with ChatGPT
• Participants create a
draft script for a
surgical procedure
or topic of their
choice using
ChatGPT.
• Copy script and edit
in word doc.
Part 2: Creating AI-
Generated Art
• Participants
generate AI art
relevant to their
video script.
• Download for use in
video
Part 3: Video
Assembly using
InVideo (40 minutes)
• Overview of InVideo
interface and
features.
• Integrating AI-
generated art and
script into a
cohesive video.
• Using text-to-speech
for narration.
107. Add SciSpace Copilot to your browser
AI research assistant that explains the text, math, and tables in
scientific literature like research papers, technical blog posts, or
reports. You can also ask follow-up questions, and it will give
you instant answers.
114. Title insights Authors Date Journal name
Asian (Bio)Values: Constructing Asian
Difference and Biovalue in the Singapore
Diabetes Discourse
The provided information does not address
the integration of Asian values into western
bioethics frameworks.
Mohammad Khamsya Bin Khidzer 21/6/2023 Science, Technology,
& Human Values
Bioethics Across the Globe: Rebirthing
Bioethics
The paper suggests discussing Bioethics in
Asia" to incorporate Asian values into the
existing framework of bioethics."
Akira Akabayashi 19/5/2020
Beyond a Western Bioethics in Asia and Its
Implication on Autonomy.
The article explores integrating Asian values
into Western bioethics frameworks,
particularly in the areas of breaking bad
news, giving consent, determining best
interests, and end-of-life care.
Mark Tan Kiak Min 8/7/2017
Translating Asian Bioethics into developing
global Biocultures Translational Challenges
In Bioethics
Hans-Martin Sass 22/12/2015 Jahr - European
journal of bioethics
Culture and ethics in medical education: The
Asian perspective.
Muhammad Shahid Shamim, Lubna
Baig, Adrienne Torda, Chinthaka
Balasooriya
1/3/2018 Journal of Pakistan
Medical Association
Bioethics as an Approach to Nanoethics in
China and the EU
Sally Dalton-Brown 1/1/2015
Bioethics in East Asia: Development and
Issues
Myongsei Sohn 1/1/2016
(East) Asia" as a Platform for Debate:
Grouping and Bioethics."
Margaret Sleeboom-Faulkner 1/1/2016 Kennedy Institute of
Ethics Journal
Western or Eastern principles in globalized
bioethics? An Asian perspective view
Michael Cheng-Tek Tai 1/3/2013 Tzu Chi Medical
Journal
Eubios Journal of Asian and International
Bioethics
Yayi Suryo Prabandari, Claire Lajaunie,
Serge Morand, Tan Boon Huan
1/1/2014
125. Practical exercise
• Use Gen AI to help with generating
content, phrasing, or grammar and
style checking as needed. Feel free to
collaborate with your peers, share
ideas, and provide feedback to each
other.
• After completing the draft, share it
with the group if you feel comfortable.
We'll discuss the drafts collectively,
providing constructive feedback and
suggestions for improvement.
• Validate the responses of ChatGPT and
incorporate in writing
• Remember, the introduction is your
chance to grab the reader's attention
and convince them of the importance
of your research, so make it engaging
and informative! (use this in your
prompts when writing the
introduction!)
126. Peer review and
Feed back
• Present your prompts and the
responses
• Show your Literature Table
• Show how you validated the
Generative AI’s response
127. Goals
• Purpose and
components of
methods
• Structure the
methods
• Typeset for methods
review
• Using ChatGPT with
prompts
128. Purpose and Structure of the Methods
Section
Explanation of
the procedures
used
Selection of
Participants
Description of
Procedures
and Materials
Data Collection
Methods
Data Analysis
Methods
Ethical
Considerations
Limitations and
Assumptions
Replicability of
the Study
129. AI Tools for RESEARCH
• Elicit for Literature Search
• Scholarcy and Typeset for data
extraction and summary
• Genei.io for summarisation and
key points highlighting
• Keyword generation with ChatGPT
( targeted prompt engineering)
140. The Art and Science of Qualitative Research
https://tinyurl.com/QUALIRE
Introduction to research in healthcare
https://tinyurl.com/HCARERE
AICHAT BT FOR Research in healthcare
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Editor's Notes
The clinical domain refers to identifying real‐world clinical needs and validating these needs throughout the life cycle of the project. Herein, the major risks, objectives and key results, and practical advice, across the three time‐phases of development, are presented.
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Infographics
Whether the watermills of millennial past, or the today's lecture room mechanics, plentiful evidence points to humanity's long history of creating a paradise to undertake a repetitive work.