Microsoft Technology Licensing, LLC

Craig Frederick Feied

Jonathan Alan Handler

Michael Todd Gillam

John Christopher Gillotte

Zhengyou Zhang

Cha Zhang

Yan Xu

Rajesh Hegde

Eric I-Chao Chang

Bryan Dove

Renato Reder Cazangi

Dobroslav K Kolev

Kurt Arley Luke Thorne

Described is a technology by which medical patient facial images are acquired and maintained for associating with a patient's records and/or other items. A video camera may provide video frames, such as captured when a patient is being admitted to a hospital. Face detection may be employed to clip the facial part from the frame. Multiple images of a patient's face may be displayed on a user interface to allow selection of a representative image. Also described is obtaining the patient images by processing electronic documents (e.g., patient records) to look for a face pictured therein.

Automated acquisition of facial images

A de-identification system is described herein for converting original messages into de-identified messages. The de-identification system leverages original message-inception-functionality which operates as a gateway for providing original messages for use by a production environment. Namely, the de-identification system includes a transformation module that receives the original messages from the original message-inception functionality. The transformation module then converts instances of sensitive information contained in the original messages into non-sensitive information, to produce the de-identified messages. A de-identified environment can consume the de-identified messages with high confidence that the messages have been properly sanitized. This is because the de-identification work has been performed at a well-contained quarantine level of the message processing functionality.

Functionality for providing de-identified data

The described implementations relate to patient identification. One implementation can acquire binary biometric data and structured data from a patient. This implementation can compare the acquired patient binary biometric data and structured data to binary biometric data and structured data associated with patient files in an electronic master patient index.

Patient identification

One or more techniques and/or systems are disclosed that provide for document retrieval where a user can identify key attributes of potential target documents that are desirable (e.g., have a particular semantic content for the user). Further, relevant documents that comprise the desired semantic content can be retrieved. Additionally, the user can provide feedback on the retrieved documents, for example, based on key semantic concepts found in the documents, and the input can be used to update the classification. For example, this process can be iterated to improve the retrieval and precision of documents found through machine learning techniques.

Semantic content searching

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Kirkland, WA, United States of America

Craig Frederick Feied