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Proceedings of the 2015 Workshop on Visual Analytics in Healthcare (VAHC '15)
| Content Provider | ACM Digital Library |
|---|---|
| Editor | Perer, Adam Bernard, Jürgen Gschwandtner, Theresia |
| Copyright Year | 2015 |
| Abstract | The vast amounts of health data poses a challenging task for clinicians as well as for data analysts when conducting comparative effectiveness or outcomes research. Information Visualization (InfoVis) and Visual Analytics (VA) have great potential to help users with this challenge. These highly interactive, visual methods can help experts explore, filter, analyze, and communicate the large and diverse data found in the modern clinical environment. For example, (a) physicians and clinical practitioners are faced with the challenging task of analyzing large amounts of unstructured, multimodal, and longitudinal data to effectively diagnose and monitor the progression of a particular disease; (b) patients are confronted with the difficult task of understanding the correlations between a broad range of clinical values and their own patient-generated health data to gain insights relevant to managing their health and wellness; and (c) healthcare and public health organizations are faced with the problem of understanding the nature of disease in broad populations, and improving overall operational performance while still maintaining the quality of patient care and safety. However, to be successful, visualization-based methods must be developed to align with the unique demands of the healthcare system. |
| Related Links | http://www.visualanalyticshealthcare.org |
| ISBN | 9781450336710 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2015-10-25 |
| Access Restriction | Subscribed |
| Content Type | Text |
| Resource Type | Conference Proceedings |
