Frontiers of AI in Medical Imaging for Clinical Decision Making
From the November 1st, 2017 Human AI Collaboration: A Dynamic Frontier Conference; Daniel Rubin, Associate Professor of Biomedical Data Science, Radiology, Medicine (Biomedical Informatics Research), and Ophthalmology (courtesy), Stanford University looks at...
1. There is much variability in people and their diseases, necessitating “precision medicine” and “precision health.”
2. There are enormous amounts of data that can be leveraged to improve clinical decision-making.
3. Integrating various types of data (e.g., images + clinical notes) and handling longitudinal data is needed.
4. AI methods that leverage integrated data can provide clinical decision support in several types of clinical decision scenarios.
From the November 1st, 2017 Human AI Collaboration: A Dynamic Frontier Conference; Daniel Rubin, Associate Professor of Biomedical Data Science, Radiology, Medicine (Biomedical Informatics Research), and Ophthalmology (courtesy), Stanford University looks at…
1. There is much variability in people and their diseases, necessitating “precision medicine” and “precision health.”
2. There are enormous amounts of data that can be leveraged to improve clinical decision-making.
3. Integrating various types of data (e.g., images + clinical notes) and handling longitudinal data is needed.
4. AI methods that leverage integrated data can provide clinical decision support in several types of clinical decision scenarios.
