There is significant unstructured clinical information found in medical images that can greatly influence patient care. We support both 2D and 3D images of various modalities and our computer vision algorithms automatically identify and extract relevant clinical features from the query image. Currently, we provide solutions for ultrasound imaging.
Since clinical experience plays a crucial role in the diagnosis of patients, we believe that being able to query for similar patients would be of significant value in both clinical practice and academic research. Our machine learning algorithms automatically retrieve similar patient records based on both structured and unstructured data using highly scalable, graph-based algorithms.
As the volume and complexity of patient data increases across healthcare organizations, retrieval of patient information cannot be solely based on textual, structured queries as it is currently done. We provide a marketplace of data visualizations so physicians can easily interact with and gain clinical insights from patient data.
There is high interobserver and intraobserver variation (based on clinical experience) in medical image analysis. Hence, a system that is personalized for a particular user would provide more relevant information for the user and a better understanding of the sources of variation. Our search engine continually learns from physicians and provides results that are personalized to the physician and contextually relevant for the current patient.
SemanticMD’s RESTful API provides an infrastructure for developers to power web applications and data-rich services, at any scale to analyze patient images. Learn from these examples how we can help you develop and maintain real-time applications with direct access to millions of patient records.
Please contact us below if you would like to work with us on any of these applications or develop your own.
Provide an easy-to-use UI for navigating patient data. WebGL technology enables rendering of 1M+ patients within seconds in the browser. Supports visual search and comparison of patient data.
Provide a dashboard with interactive data visualizations for radiology managers and administrators to measure key workflow analytics (number of readings, turnaround time, peer review data, etc.).
Enable web-based, zero footprint viewing and annotation of ultrasound images. Our secure servers store the images along with the annotations in an easily retrievable form.
Adam worked as a software architect and systems administrator at the University of Pittsburgh Drug Discovery Institute where he managed a team to build an open source, scalable and fault-tolerant distributed data analytics platform for the NIH. This web-based platform provides predictions and clinical insights into in-vivo drug trials in human organs based on experimental microphysiological device readings and known human drug-organ interactions.