Winter Quarter – Academic Year 2023/2024
| Instructors | https://profiles.stanford.edu/oliver-aalami (Lead) https://guestrin.su.domains/ (CS Lead)
https://profiles.stanford.edu/andreas-bauer https://profiles.stanford.edu/vasiliki-bikia https://profiles.stanford.edu/adrit-rao https://profiles.stanford.edu/vishnu-ravi?tab=bio https://profiles.stanford.edu/schmiedmayer https://profiles.stanford.edu/zagar https://profiles.stanford.edu/aydin-zahedivash | | --- | --- | | Contact | mailto:[email protected] | | Units | 3-4 units | | Day/Time | Tuesdays and Thursdays from 4:30 PM - 6:00 PM | | Location | Tuesdays https://25live.collegenet.com/pro/stanfordsom#!/home/location/731/details; Thursdays https://25live.collegenet.com/pro/stanfordsom#!/home/location/1144/details (except last two https://25live.collegenet.com/pro/stanfordsom#!/home/location/1145/details) In person attendance is recommended! Zoom is offered as a backup. Link to Zoom found in Canvas! | | Course Material | https://canvas.stanford.edu/courses/183525 & https://github.com/CS342 |
As our world becomes more and more digitized, patients and their devices are generating streams of valuable data that can provide meaningful clinical insights. This digital health revolution provides great opportunities to design and validate new digital health concepts. Many groups within Stanford Medicine have promising ideas that are ripe for development, however, they lack the software engineering and healthcare compliance know-how to take them forward.
Building for Digital Health is a Biodesign course sponsored by the Stanford School of Medicine (SoM) and Stanford’s Computer Science (CS) department. Its goal is to provide CS students with the opportunity to apply their skills to real-world health technology development projects, while enabling SoM faculty to leverage these talented individuals to help advance their technology concepts toward patients. Both audiences will learn a repeatable approach for developing new digital health technologies and preparing to launch them in the market.
Over the course of ten weeks, students and faculty will work together to tackle a project and launch an app-enabled solution for research use. Every week, students will learn about app-development, sensor technologies, privacy, security, and more. In the final week of class, teams will present their final project (app) to a panel of digital health experts.
https://lh5.googleusercontent.com/OozprhleATEMtnae30pauzCwqpiXnByRFQ-Dr2XhcnBQPj8a0E6krurdupGEm1xlxb6tg3ZX2lFh3eA_W9ANobDUAmLAwGLGP4Ync0ykObkN6BO9WFHvV7pJ7WUZYBChnEOoG6XmB2sqdUkRDB8PVYo
Mobile Application Development (iOS, watchOS, visionOS)
Learn about what makes the mobile operating systems as powerful platforms to develop clinical apps. Overview of open source frameworks leverage Apple technologies to accelerate medical research.
Open Source + Using GitHub
Become familiar with using GitHub to manage software development projects. Learn how to contribute to open-source projects, collaborate on software, automatically test, and build high-quality systems.
https://lh5.googleusercontent.com/K2SjIU6uVUVwgWdAWVeweJDzQ_QF2cNBAW_GiUkjcTtc8Aaw5MbppR9gwTUL6hbezReIjlq-kd0yhkvupVNpaSvwTzxMDipSBXcruLSvKVNXEPXiaGan5QAOOq5eTzkj1TBL8QXGoM7_qpSi1yiS6xk
Stanford Spezi
Spezi's ecosystem of modules designed for digital health applications makes it easy to build your own app including questionnaires, data collection from wearable devices, and integration with electronic health record systems. Spezi apps use HL7 FHIR as their native data standard for interoperability. Spezi is free and open-source under the MIT license.
AI & Large Language Models
Machine learning, generative AI such as large language models, and time series data analysis are crucial for modern digital health applications. You will learn how to execute ML models locally on a device to ensure privacy and security and how to use patience-centric AI to support digital health innovations.
Using Apple Technologies and Frameworks
We will use HealthKit to read health and activity data from the iPhone. This enables providers to track a patient’s step count, heart rate, flights climbed, calories burned, and other similar metrics over time. HealthKit also allows us to download electronic health records (EHR) to your iPhone using the Fast Healthcare Interoperability Resources (FHIR) specification.
https://lh5.googleusercontent.com/LjxEoxY3S-2DUNTXTGVkM1Ak3yhX0LB97w5G8bSSNdGEIBd0G7m3FVeQUqphqJYaT2ldoaBZkeJvcOjh1EbF9LwuAJeSXuugdbz5oZNHWpDiZRQe_LwtjXKRmc-PzsVU9nqEWMtZfofckD_2e0gU_CE