Final project writeups can be at most 5 pages long (including appendices and figures). Probabilistic Graphical Models. Current Projects Below is a list of our ongoing collaborations with both internal and external organizations working on healthcare AI implementations. Ultimately we need to develop machine intelligence that understands human language, emotions, intentions, behaviors, and interactions at multiple scales. (Is this project applying a common technique to a well-studied problem, or is the problem or method relatively unexplored?). In the proposal, below your project title, include the project category. Please refer to the course schedule page for information about deadlines. in contributions and evaluations when assigning project grades. and/or algorithms? Read and view relevant articles and presentations stemming from our collaborations using the button below. Motivation: What problem are you tackling, and what's the setting you're considering? Of course, depending on the topic of Current AI systems lack flexibility and contextual understanding, and resist explanation in terms comprehensible by humans. Is this an application or a theoretical result? Sutton and Barto. Projects & innovations. (Just be sure to ask us for help if you're uncertain how to best get started.) The category can be one of: Your proposal should be a PDF document, giving the title of the project, the project category, the full names of all of your team members, the SUNet ID of your team members, and a 300-500 word description of what you plan to do. In a three-person team this can be shared much better, Please read below for a description of our ongoing medical VR projects. Motivation: What problem are you tackling? encourage you to collaborate with non-Stanford people for the course project due to potential IP implications (Stanford owns the IP for all technology that’s developed as a result of course projects). For shared projects, we also require that you submit the final report from the In exceptional cases, we can allow a team of 4 people. As long as your proposal follows the instructions above and the project seems to have been thought out with a reasonable The final report will be judged based off of the clarity of the report, the relevance of the project to topics taught in CS229, the novelty of the problem, and the technical quality and significance of the work. Once you have identified a topic of interest, it can be useful to look up existing research on relevant topics by searching related keywords on an academic search engine such as: http://scholar.google.com. Alternatively the teams can coordinate to make sure they work on different This course will introduce you to mixed signal design and the electronic design automation (EDA) tools used for it. The final project is intended to start you in these directions. Similar to to the proposal, it should include. The technical quality of the work. your project teammates, please create a private Piazza post. Stanford AI4ALL aims to increase diversity in the field of Artificial Intelligence. don't allow for it, you cannot do it. You do not have to include the data or additional libraries (so if you submit a zip file, it should not exceed 5MB). Please include a section that describes what each team member worked on and contributed to the project. Your milestone should be at most 3 pages, excluding references. about! During this three-week residential program, students are immersed in AI through a combination of lectures, hands-on research projects, field trips, and mentoring activities. Please first have a look through the frequently asked questions. Start or advance your journey in AI through a pre-college AI program for high school students. Note: We will not be holding a poster session in Fall 2020. If that data needs considerable pre-processing  to suit your task, or that you intend to collect the needed and the NIPS deadline is usually in early June (http://nips.cc/). Like many forward-thinking doctors, Ron Li, MD, clinical assistant professor of hospital medicine and biomedical informatics, believes that AI and machine learning have an important place in the future of medicine. Support Lucile Packard Children's Hospital Stanford and child and maternal health. Support teaching, research, and patient care. Be brave rather than timid, and do feel free to propose ambitious things that you're excited about. “The future of AI must be informed by experts from a range of disciplines, working together with a shared purpose to guide the technology towards greater public good,” said Deep Ganguli, Director of Research for Stanford HAI. This is the third year HAI has distributed seed grants across the university to fund new, ambitious, and speculative ideas with the allowing the team to focus a lot more on the interesting stuff, e.g. For group-specific questions regarding projects, please create a private post on … Stanford AI Lab. Stanford Center for AI Safety researchers will use and develop open-source software, and it is the intention of all Center for AI Safety researchers that any software released will be released under an open source model, such as BSD. CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning Pranav Rajpurkar*, Jeremy Irvin*, Kaylie Zhu, Brandon Yang, Hershel Mehta, Tony Duan, Daisy Ding, Aarti Bagul, Curtis Langlotz, Katie Shpanskaya, Matthew P. Lungren, Andrew Y. Ng Matt S. Creative Director. We may reach out and factor Stanford’s Susan Athey discusses the extraordinary power of machine-learning and AI techniques, allied with economists’ know-how, to answer real-world business and policy problems. You must submit a written proposal for a 4-person project to co-head TA Michael Zhu, which has to be approved. Note: Only one group member is supposed to submit the assignment, and tag the rest of the group members (do not all submit separately, or on the flip side forget to tag your teammates if you are the group's designated submitter). During this three-week online program, students are immersed in AI through a combination of lectures, hands-on research projects, and mentoring activities. Communication: We will use Piazza for all communications, and will send out an access code through Canvas.We encourage all students to use Piazza, either through public or private posts. We don't mind you using a dataset that is not public, as long as you have the required permissions to use it. Stanford AI4ALL aims to increase diversity in the field of Artificial Intelligence. Siddharth K. Web Developer. at least a week in advance of the final submission deadline. If you're looking for project ideas, please come to office hours, and we'd be happy to brainstorm and suggest some project ideas. https://icml.cc/Conferences/2019/Schedule, https://neurips.cc/Conferences/2019/Schedule. Most students do one of three kinds of projects: Many fantastic class projects come from students picking either an application area that they're interested in, or picking some subfield of machine learning that they want to explore more. We analyzed our data gathered through interviews and derived key insights and inferences. (Did the authors choose an interesting or a “real" problem to work on, or only a small “toy" problem? Each year, some number of students continue working on their projects after completing CS229, submitting their work to a conferences or journals. Two of the main machine learning conferences are ICML and NIPS. Also check out Google Colab for free GPU resources. ), The novelty of the work. A very good CS229 project will be a publishable or nearly-publishable piece of work. Submission: We’ll be using Gradescope for submission of all four parts of the final project. professor) had advised you on this work, your write-up must fully acknowledge their contributions. Co-designed the "NLP in Medicine" workshop for the 58th Annual Meeting of the Association for Computational Linguistics in July 2020, and now working together to explore areas and ideas for broader study and development with Amazon, Identifying high value projects to advance AI and ML solutions to critical challenges in primary care and mentoring physician innovators through the AAFP Primary Care Innovation Fellowship, Studying the feasibility and acceptability of a medical analytics platform powered by machine learning and natural language processing to deliver capabilities spanning population health, cohort discovery, predictive analytics, remote patient monitoring, and clinical decision support with Codex Health, Assessing the current landscape of remote patient monitoring tools and technologies to determine the key features of success and needs that remain unmet, Co-designed and conducted a survey with DeepScribe to explore provider experiences and attitudes towards emerging technologies that aim to assist providers by automating certain aspects of clinical documentation, Exploring the utility and promise of applying AI to healthcare, including technology-enabled documentation and tools to support care delivery with Google Health, Designing and assessing the feasibility and acceptability of a health AI marketplace platform that streamlines the AI deployment pipeline for health systems, Developing a national telemedicine curriculum for medical students, residents, and teaching clinicians as part of STFM's National Telemedicine Task Force, Read this article and this paper to learn more about this project, Assessing the feasibility and efficacy of detecting stress in family medicine practitioners through desktop computer interactions with CARS, Implementing a predictive mortality model to enable patient selection for end of life advance care planning discussions and increase the incidence of documented conversations at Stanford Health Care with BMIR, Read this article and this paper to learn more about this project, Developing AI-driven clinical order recommendations for primary care physicians to tee up appropriate and efficient specialty care consultations, Studying the feasibility of developing an AI algorithm that can predict depression and anxiety based on audio and visual cues captured from a recording of the person with CERC, Advising a project assessing the feasibility and acceptability of leveraging at-home voice applications to assist patients with insulin-dependent diabetes management remotely, Completed a comprehensive environmental scan, a literature review, and key informant interviews to explore the use of AI in pre-visit planning with the ESU, Collaborating with MCiM - a master's program for working professionals seeking to harness the power of digital innovations in healthcare - to provide a management-focused educational experience and foster digitally-driven excellence in healthcare, Developing high-performance open source clinical identification tools that enable researchers around the world to use clinical text for AI-driven applications while preserving patient privacy with Research IT, Implementing a predictive model for clinical deterioration in the inpatient acute care setting to reduce unexpected escalations to the intensive care units and mortality at Stanford Health Care and Valley Care, Read this article to learn more about this project, Collaborating with SMCI as active affiliate faculty and guest lecturers in order to foster a culture of continuous improvement across Stanford Medicine, Lucile Packard Children's Hospital Stanford. Intended experiments: What experiments are you planning to run? That said, you can always consult a TA you are unsure about any method or problem statement. A team can have both on-campus and SCPD students. data yourself, keep in mind that this is only one part of the expected project work, but can often take considerable time. Please include a link to a Github repository or zip file with the code for your final project. Below is a list of our ongoing collaborations with both internal and external organizations working on healthcare AI implementations. Preliminary experiments: Describe the experiments that you've run, the outcomes, and any error analysis that you've done. You can find papers from the recent ICML https://icml.cc/Conferences/2019/Schedule and NeurIPS conference https://neurips.cc/Conferences/2019/Schedule. Method: What machine learning techniques are you planning to apply or improve upon? We propose an Ethics Review Board (ERB), a process for providing feedback to researchers as a precondition to receiving funding from a major on-campus AI institute. Design Process. Clearly indicate in your milestone and final report, which part of the project is done for CS229 and which part is done for a class other than CS229. in mind that the intended audience are the instructors and the TAs. If you have any concerns working with one of If you choose to collaborate you might also look at some recent machine learning research papers. 1 or 2), so keep in mind that all projects require to spend a decent minimum effort towards gathering data, and setting up the infrastructure to reach some form of result. You can write it as if you're writing the first few pages of your final project report, so that you can re-use most of the milestone text in your final report. This is to make sure team members are carrying a fair share of the work for projects. This extends to projects that were done in collaboration with research groups as well. Koller and Friedman. For shared projects, we also require that you submit the final report from the class you're sharing the project with. Here is a short list of these projects. No, we don't restrict you to only use methods/topics/problems taught in class. For group-specific questions regarding projects, please create a private post on Piazza. Download; Point of View. Artificial intelligence (AI) research is routinely criticized for failing to account for its long-term societal impacts. The Green Button project Artificial Intelligence: A Modern Approach. We are looking into getting cloud credit for the projects. Late days cannot be used for the project. If you plan to work on a project in a team of 4, please come talk to one of the TAs beforehand so we can ensure that the project has a large enough scope. In particular, we expect the team to submit a completed project (even for team of About. Prerequisites: Students should be interested in AI research/applications, and be interested in technical and human-centric implications of AI applications. You should have tried at least one baseline. Some of the potential projects will include data visualization and education platforms, improved modelling and predictions, social network and NLP analysis of the propagation of COVID-19 information. Based off of the topic you choose in your proposal, we’ll suggest a project mentor given the areas of expertise of the TAs. The Stanford Artificial Intelligence Laboratory (SAIL) has been a center of excellence for Artificial Intelligence research, teaching, theory, and practice since its founding in 1962. Projects. ML/AI background: You have a solid background in probability and linear algebra, and have done well in AI/ML coursework. Exposure to AI through projects, and mentoring activities design and the TAs team members enrolled in CS229 in milestone. 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