Natural language processing (NLP) has become essential for secondary use of clinical data. Over the last two decades, many clinical NLP systems were developed in both academia and industry. However, nearly all existing systems are restricted to speci...
Breast lesion detection employing state of the art microwave systems provide a safe, non-ionizing technique that can differentiate healthy and non-healthy tissues by exploiting their dielectric properties. In this paper, a microwave apparatus for bre...
Clinical trials consume the latter half of the 10 to 15 year, 1.5-2.0 billion USD, development cycle for bringing a single new drug to market. Hence, a failed trial sinks not only the investment into the trial itself but also the preclinical developm...
Stakeholders across the entire healthcare chain are looking to incorporate artificial intelligence (AI) into their decision-making process. From early-stage drug discovery to clinical decision support systems, we have seen examples of how AI can impr...
OBJECTIVES: To develop a deep learning-based algorithm to automatically identify optimal portal venous phase timing (PVP-timing) so that image analysis techniques can be accurately performed on post contrast studies.
OBJECTIVE: Artificial intelligence (AI) provides people and professionals working in the field of participatory health informatics an opportunity to derive robust insights from a variety of online sources. The objective of this paper is to identify c...
Predicting the response, or sensitivity, of a clinical drug to a specific cancer type is an important research problem. By predicting the clinical drug response correctly, clinicians are able to understand patient-to-patient differences in drug sensi...