| Both sides previous revision
Previous revision
Next revision
|
Previous revision
Next revision
Both sides next revision
|
start [2022/09/05 16:53]
nigam |
start [2022/09/23 15:47]
nigam |
| We **answer clinical questions** to enable better medical decisions using EHR and Claims data, via a bedside consult service that enables the use of aggregate patient data at the [[http://stanmed.stanford.edu/2016winter/on-the-button.html|point of care]]. Check out our [[:greenbutton| Informatics Consult Service]] that puts this [[https://shahlab.stanford.edu/greenbutton_idea| idea]] in action. | We **answer clinical questions** to enable better medical decisions using EHR and Claims data, via a bedside consult service that enables the use of aggregate patient data at the [[http://stanmed.stanford.edu/2016winter/on-the-button.html|point of care]]. Check out our [[:greenbutton| Informatics Consult Service]] that puts this [[https://shahlab.stanford.edu/greenbutton_idea| idea]] in action. |
| |
| We **make predictions** that allow taking mitigating actions. We [[https://arxiv.org/abs/2007.10306|characterize the fairness]] and examine the [[https://www.nejm.org/doi/full/10.1056/NEJMp1714229|ethical implications]] of using machine learning in clinical care. We have built models for predicting [[http://bmjopen.bmj.com/cgi/content/full/bmjopen-2016-011580?ijkey=oCxNIjOhCzOdmR8&keytype=ref| future increases in cost]], identifying [[http://www.ncbi.nlm.nih.gov/pubmed/26606167| slow healing wounds]], [[http://www.ncbi.nlm.nih.gov/pubmed/24988898|missed diagnoses of depression]] and for [[http://stanmed.stanford.edu/2018summer/artificial-intelligence-puts-humanity-health-care.html| improving palliative care]]. Check out our [[:aihc| Program for AI in Healthcare]] | We **make predictions** that allow taking mitigating actions, while maintaining the [[https://stanmed.stanford.edu/artificial-intelligence-puts-humanity-health-care/ human touch in patient care]]. Check out our [[:aihc| Program for AI in Healthcare]] and the [[:datascience | Applied Data Science team]] that puts these ideas in action. |
| |
| We develop methods to analyze multiple datatypes for **generating insights**. Such as: | We develop methods to analyze multiple datatypes for **generating insights**. Such as: |
| * [[:biomedin215|BIOMEDIN 215]], taught for the BMI Graduate program is designed to prepare you to pose and answer meaningful clinical questions using routinely collected healthcare data. | * [[:biomedin215|BIOMEDIN 215]], taught for the BMI Graduate program is designed to prepare you to pose and answer meaningful clinical questions using routinely collected healthcare data. |
| * [[:biomedin225|BIOMEDIN 225]], taught for the MCiM program explores how to use electronic health records (EHRs) and other patient data in conjunction with recent advances in artificial intelligence (AI) and evolving business models to improve healthcare. | * [[:biomedin225|BIOMEDIN 225]], taught for the MCiM program explores how to use electronic health records (EHRs) and other patient data in conjunction with recent advances in artificial intelligence (AI) and evolving business models to improve healthcare. |
| * [[https://hai.stanford.edu/safe-ethical-and-cost-effective-use-ai-healthcare-critical-topics-senior-leadership|Safe, Ethical, and Cost-Effective Use of AI in Healthcare: Critical Topics for Senior Leadership]], taught in partnership with the Institute for Human-Centered AI (HAI) and the Center for Artificial Intelligence in Medicine & Imaging (AIMI). | |
| * [[https://www.coursera.org/specializations/ai-healthcare/|AI in Healthcare Specialization on Coursera]], created in partnership with the [[https://healtheducation.stanford.edu/|Stanford Center for Health Education]]. The course reviews the current and future applications of AI in healthcare with the goal of learning to bring AI technologies into the clinic safely and ethically. | * [[https://www.coursera.org/specializations/ai-healthcare/|AI in Healthcare Specialization on Coursera]], created in partnership with the [[https://healtheducation.stanford.edu/|Stanford Center for Health Education]]. The course reviews the current and future applications of AI in healthcare with the goal of learning to bring AI technologies into the clinic safely and ethically. |
| * [[https://stanfordmlgroup.github.io/programs/aihc-bootcamp/|AI in Healthcare Bootcamp]], provides students an opportunity to do cutting-edge research at the intersection of AI and healthcare | * [[https://stanfordmlgroup.github.io/programs/aihc-bootcamp/|AI in Healthcare Bootcamp]], provides students an opportunity to do cutting-edge research at the intersection of AI and healthcare |
