Mary M. Saltz

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Increased accessibility of health data provides unique opportunities to discover spatio-temporal patterns of diseases. For example, New York State SPARCS (Statewide Planning and Research Cooperative System) data collects patient level detail on patient demographics, diagnoses, services, and charges for each hospital inpatient stay and outpatient visit. Such(More)
Cancer is a complex multifactorial disease state and the ability to anticipate and steer treatment results will require information synthesis across multiple scales from the host to the molecular level. Radiomics and Pathomics, where image features are extracted from routine diagnostic Radiology and Pathology studies, are also evolving as valuable(More)
The financial incentives for data science applications leading to improved health outcomes, such as DSRIP (bit.ly/dsrip), are well-aligned with the broad adoption of Open Data by State and Federal agencies. This creates entirely novel opportunities for analytical applications that make exclusive use of the pervasive Web Computing platform. The framework(More)
Well-curated sets of pathology image features will be critical to clinical studies that aim to evaluate and predict treatment responses. Researchers require information synthesized across multiple biological scales, from the patient to the molecular scale, to more effectively study cancer. This article describes a suite of services and web applications that(More)
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