Stanford Technology in Healthcare
Fall 2024 Internship
Partnering with Patients to Innovate for the Future
Course Faculty and Instructors
- Larry Chu, MD
Professor of Anesthesiology, Perioperative and Pain Medicine - Dara Rouholiman, BS
Machine Learning Engineer, Course Lead Instructor, AIM Lab, Department of Anesthesiology, Perioperative and Pain Medicine
A Fall 2024 Stanford Internship from SASI
Embark on an 4-week virtual journey that delves deep into the innovative world where technology meets healthcare.
This course is not just an educational pursuit; it's a visionary exploration into how innovative technologies can transform patient care and medical research, with a special spotlight on anesthesiology. At the heart of academic excellence lies the power of diversity and the spirit of inclusion.
Guest Speakers
Bob Messerschmidt
Bob Messerschmidt is a digital health futurist and serial entrepreneur with 30 years in health, optics, and spectroscopy. He sold his last company to Apple, where he helped architect the Apple Watch’s health technologies.
Robin Diane Goldstein
A leader with decades of experience in tech, Robin has held roles at Sony, Zoox and Apple, including Senior Manager of Health Special Projects. An MIT graduate, she advises startups and serves as a Biodesign mentor.
Corinna Zygourakis, MD
Dr. Zygourakis a leader in minimally invasive and robotic spinal surgery, and her research on using wearable tech like the Apple Watch to improve patient outcomes exemplifies how cutting-edge technology can directly impact patient care.
"Embark on a path that clarifies your future. This course guides students exploring careers and seeking direction.
Course Description
Welcome to "Technology in Healthcare: Partnering with Patients to Innovate for the Future," an 4-session virtual internship designed to bridge the gap between cutting-edge technologies and practical healthcare applications.
This course offers a deep dive into the world of health care technologies, with a special focus on its applications in anesthesiology. Over the course of four weeks, students will explore how innovative technologies are revolutionizing the field of healthcare, transforming patient care and medical research.
Key Highlights
- Hands-On Patient Interaction: Experience direct interaction with real patients, gaining insights into their unique healthcare challenges.
- Patient-Centered Technology Applications: Discover how to apply new technologies in real-world, patient-focused scenarios, bridging technology with compassionate care.
- Expert-Led Insights: Engage with seasoned professionals and experts in technology and healthcare, providing a well-rounded understanding of the field.
Learning Objectives
The course is structured to achieve the following key learning objectives:
- Understanding Basic ML Concepts: Gain a foundational understanding of key ML algorithms and terminology, setting the stage for more advanced topics.
- Comprehending Ethical Implications: Critically examine the ethical considerations in employing new technologies in healthcare, understanding the balance between technological innovation and ethical responsibility.
Course Dates and Curriculum
Target Audience
Who is This Course For?
This course is designed to welcome a broad spectrum of high school students with varied interests and skills. Ideal candidates include:
- Aspiring Healthcare Professionals: Students passionate about entering the healthcare field and eager to integrate emerging technologies like machine learning into patient care.
- Budding Technologists: Young innovators who are curious about the potentials of machine learning, even without prior coding experience.
- Innovative Thinkers: Individuals who think outside the box, capable of approaching complex problems with creative solutions.
- Ethical Leaders: Students who recognize the importance of ethical considerations in technology and healthcare, aiming to be future leaders who can balance innovation with ethical responsibility.
- Team Players: Those who excel in collaborative environments, as the course emphasizes a team-based project approach, allowing for various non-technical roles.
Prerequisites
Baseline Knowledge and Skills
The course is tailored to accommodate a range of backgrounds and does not require advanced technical skills. The following are the baseline prerequisites:
- Basic Computer Literacy: Comfort with using computers and navigating online platforms is essential.
- Interest in Machine Learning and Healthcare: A keen interest in learning about machine learning and its application in healthcare is crucial.
- Teamwork Skills: As the course involves team-based projects, the ability to collaborate effectively with peers is important.
- Open-mindedness: Willingness to engage with new concepts and participate in discussions and practical projects.
Optional but Beneficial
- Basic Understanding of Algebra and Statistics: Helpful for grasping some ML concepts, but not mandatory.
- General Science Knowledge: Familiarity with basic scientific principles can be advantageous, particularly for understanding healthcare applications.
- Curiosity and Enthusiasm: An eagerness to explore new ideas and the ambition to apply them in real-world scenarios.
Course Methods
Each week of this 4-week course is designed to progressively deepen your understanding and skills in health care technologies and its application in healthcare.
- Week 1: Welcome and Course Introduction
The first week provides an overview of course objectives and structure, introduces the instructors and participants, covers the current state of technology in health care, and includes interactive workshops on telemedicine and EHR systems. - Week 2: Artificial Intelligence and Machine Learning in Health Care
This week covers AI and ML fundamentals, their applications in diagnostics and treatment planning, cases tudies on AI in radiology, and interactive workshops on building predictive models and exploring AI tools. - Week 3: Robotics and Wearable Technology in Health Care
The third week discusses the use of robotics in surgery and patient care, wearable technology for chronic disease management, and includes workshops on designing wearable health monitors and practicing with robotic surgery simulators. - Week 4: Future Trends and Ethical Considerations in Health Technology
The final week explores emerging health technologies, ethical issues in health technology, includes workshops on ethical decision-making, and concludes with a group activity to create a vision for the future of health technology.
Interactive Elements
Dynamic Lectures: Engage in lectures that are not just informative but also interactive, encouraging active participation and discussion.
Hands-On Tasks: Apply your knowledge through practical tasks, from data analysis to model building, in a supportive learning environment.
Group Discussions: Participate in lively group discussions, fostering collaborative learning and diverse perspectives.
Personalized Mentoring
- Expert Guidance: Receive personalized mentorship from experienced professionals in ML and healthcare, ensuring that you get the support and insights needed for your learning journey.
- Tailored Feedback: Each student receives individualized feedback, particularly in project development phases, ensuring a learning experience that is aligned with your personal and professional goals.