Publications by authors named "Craig Morioka"

Objective: To partially address the opioid crisis, some complementary and integrative health (CIH) therapies are now recommended for chronic musculoskeletal pain, a common condition presented in primary care. As such, health care systems are increasingly offering CIH therapies, and the Veterans Health Administration (VHA), the nation's largest integrated health care system, has been at the forefront of this movement. However, little is known about the uptake of CIH among patients with chronic musculoskeletal pain.

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Our work facilitates the identification of veterans who may be at risk for abdominal aortic aneurysms (AAA) based on the 2007 mandate to screen all veteran patients that meet the screening criteria. The main research objective is to automatically index three clinical conditions: pertinent negative AAA, pertinent positive AAA, and visually unacceptable image exams. We developed and evaluated a ConText-based algorithm with the GATE (General Architecture for Text Engineering) development system to automatically classify 1402 ultrasound radiology reports for AAA screening.

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Advanced liver disease has long been associated with cerebral abnormalities. These abnormalities, termed acquired hepatocerebral degeneration, are typically visualized as T1 weighted hyperintensity on MRI in the deep gray matter of the basal ganglia. Recent reports, however, have demonstrated that a subset of patients with chronic alcoholic liver disease may also develop white matter abnormalities.

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Objective: Many tasks in natural language processing utilize lexical pattern-matching techniques, including information extraction (IE), negation identification, and syntactic parsing. However, it is generally difficult to derive patterns that achieve acceptable levels of recall while also remaining highly precise.

Materials And Methods: We present a multiple sequence alignment (MSA)-based technique that automatically generates patterns, thereby leveraging language usage to determine the context of words that influence a given target.

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Sentences and phrases that represent a certain meaning often exhibit patterns of variation where they differ from a basic structural form by one or two words. We present an algorithm that utilizes multiple sequence alignments (MSAs) to generate a representation of groups of phrases that possess the same semantic meaning but also share in common the same basic word sequence structure. The MSA enables the determination not only of the words that compose the basic word sequence, but also of the locations within the structure that exhibit variation.

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Careful examination of the medical record of brain-tumor patients can be an overwhelming task for the neuroradiologist. The number of clinical documents alone may approach 100 for a patient that has a 3-year-old brain tumor. The neuroradiologist's evaluation of a patient's brain tumor involves examining the current imaging exam and checking for previous imaging exams that may occur pre- or post-treatment.

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Our research addresses how to improve physician to physician communication of patient information, and how to prevent lapses of patient care as they are referred to other clinicians within the healthcare system. The wet read consultation is defined as a rapid response to a clinical question posed by a referring physician to a clinical specialist. This research involves the development of an imaging-based wet read consultation system called StructConsult (SC), which facilitates communication between non-imaging specialist (i.

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The communication of imaging findings to a referring physician is an important role of the radiologist. However, communication between onsite and offsite physicians is a time-consuming process that can obstruct work flow and frequently involves no exchange of visual information, which is especially problematic given the importance of radiologic images for diagnosis and treatment. A prototype World Wide Web-based image documentation and reporting system was developed for use in supporting a "communication loop" that is based on the concept of a classic "wet-read" system.

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The development of comprehensive picture archive and communication systems (PACS) has mainly been limited to proprietary developments by vendors, though a number of freely available software projects have addressed specific image management tasks. The openSourcePACS project aims to provide an open source, common foundation upon which not only can a basic PACS be readily implemented, but to also support the evolution of new PACS functionality through the development of novel imaging applications and services. openSourcePACS consists of four main software modules: 1) image order entry, which enables the ordering and tracking of structured image requisitions; 2) an agent-based image server framework that coordinates distributed image services including routing, image processing, and querying beyond the present digital image and communications in medicine (DICOM) capabilities; 3) an image viewer, supporting standard display and image manipulation tools, DICOM presentation states, and structured reporting; and 4) reporting and result dissemination, supplying web-based widgets for creating integrated reports.

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A patient's electronic medical record contains a large number of medical reports and imaging studies. Identifying the relevant information in order to make a diagnosis can be a time consuming process that can easily overwhelm the physician. Summarizing key clinical information for physicians evaluating brain tumor patients is an ongoing research project at our institution.

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Extracting key concepts from clinical texts for indexing is an important task in implementing a medical digital library. Several methods are proposed for mapping free text into standard terms defined by the Unified Medical Language System (UMLS). For example, natural language processing techniques are used to map identified noun phrases into concepts.

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Reviewing brain tumor patients' complete medical record is a daunting task for any clinician. In current practice, the radiologist examines the most recent documents and then dictates an assessment of the patient's condition based on a review of the most current imaging study and compared with the most recent previous image study. Occasionally, the radiologist searches other clinical documents when more precise detail is needed.

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We have developed a system to structure free-text neuroradiology reports using a natural language processing program and formatted the output into the digital image and communication in medicine (DICOM) standard for structured reporting (SR). DICOM SR formats the correspondence of pertinent diagnostic images to the radiologist's dictated report of clinical findings. In addition, DICOM SR allows the information to be organized into a tree structure.

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This review of medical imaging informatics is a survey of current developments in an exciting field. The focus is on informatics issues rather than traditional data processing and information systems, such as picture archiving and communications systems (PACS) and image processing and analysis systems. In this review, we address imaging informatics issues within the requirements of an informatics system defined by the American Medical Informatics Association.

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Following a requirements analysis for development of an information infrastructure supporting evidence-based radiology, the objective of this study was the development of a data gateway to support flexible access to the totality of a patient's electronic medical records through a single, uniform representation, regardless of the underlying data sources (eg, hospital information systems [HIS], radiology information systems [RIS], picture archiving and communication systems [PACS]). XML-based (eXtensible Markup Language) technologies were employed to create an application framework permitting querying of different clinical databases. The contents of different data sources were represented by using XML.

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Multiframe quantitative coronary angiography is typically performed by averaging measurements of artery diameter over multiple frames. This approach reduces errors attributable to random noise but may not reduce systematic errors caused by background structures, nonlinear system response, and motion blur. We attempt to reduce these sources of error by decomposing the image sequence into moving layers, one of which includes the artery.

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