Medical Photography Underutilized as a Clinical Tool: Key Considerations for Better Adoption (Preprint)

2022 ◽  
Author(s):  
Shannon Wongvibulsin ◽  
Kristian Feterik
Keyword(s):  
Clinical Tool ◽  
Medical Photography

UNSTRUCTURED NA

Ethnogeriatrics: Development and Application of the Cohort Analysis Tool

2014 ◽  
Vol 21 (2) ◽  
pp. 37-52
Author(s):  
Melen McBride
Keyword(s):  
Healthcare Professionals ◽  
Cohort Analysis ◽  
Analysis Tool ◽  
Speech Language Pathology ◽  
Clinical Tool ◽  
Research Activities ◽  
Key Concepts ◽  
Practice Teaching ◽  
Language Pathology ◽  
Significant Factors

Ethnogeriatrics is an evolving specialty in geriatric care that focuses on the health and aging issues in the context of culture for older adults from diverse ethnic backgrounds. This article is an introduction to ethnogeriatrics for healthcare professionals including speech-language pathologists (SLPs). This article focuses on significant factors that contributed to the development of ethnogeriatrics, definitions of some key concepts in ethnogeriatrics, introduces cohort analysis as a teaching and clinical tool, and presents applications for speech-language pathology with recommendations for use of cohort analysis in practice, teaching, and research activities.

Reliability of the Conversational Interaction Coding Form When Applied to Natural Conversation of Individuals With Aphasia

2010 ◽  
Vol 20 (4) ◽  
pp. 125-135 ◽  
Author(s):  
Ashley Pozzolo Coote ◽  
Jane Pimentel
Keyword(s):  
Best Practice ◽  
Interobserver Reliability ◽  
Training Session ◽  
Clinical Tool ◽  
Group Setting ◽  
Conversational Interaction ◽  
Video Recordings ◽  
Aphasia Therapy ◽  
Natural Conversation ◽  
Point To Point

Purpose: Development of valid and reliable outcome tools to document social approaches to aphasia therapy and to determine best practice is imperative. The aim of this study is to determine whether the Conversational Interaction Coding Form (CICF; Pimentel & Algeo, 2009) can be applied reliably to the natural conversation of individuals with aphasia in a group setting. Method: Eleven graduate students participated in this study. During a 90-minute training session, participants reviewed and practiced coding with the CICF. Then participants independently completed the CICF using video recordings of individuals with non-fluent and fluent aphasia participating in an aphasia group. Interobserver reliability was computed using matrices representative of the point-to-point agreement or disagreement between each participant's coding and the authors' coding for each measure. Interobserver reliability was defined as 80% or better agreement for each measure. Results: On the whole, the CICF was not applied reliably to the natural conversation of individuals with aphasia in a group setting. Conclusion: In an extensive review of the turns that had high disagreement across participants, the poor reliability was attributed to inadequate rules and definitions and inexperienced coders. Further research is needed to improve the reliability of this potentially useful clinical tool.

Electropalatography as a Research and Clinical Tool

2007 ◽  
Vol 17 (1) ◽  
pp. 7-13 ◽  
Author(s):  
Fiona E. Gibbon ◽  
Alice Lee
Keyword(s):  
Clinical Tool

Developments in 3D Echocardiography

2009 ◽  
Vol 5 (2) ◽  
pp. 10 ◽  
Author(s):  
Jose Luis Zamorano ◽  
Keyword(s):  
3D Echocardiography ◽  
Resonance Imaging ◽  
Clinical Tool ◽  
3D Images ◽  
Processing Power ◽  
2D Echocardiography ◽  
Automated Quantification ◽  
Heart Cycle ◽  
Functional Mechanisms ◽  
Full Volume

3D echocardiography (3DE) will gain increasing acceptance as a routine clinical tool as the technology evolves due to advances in technology and computer processing power. Images obtained from 3DE provide more accurate assessment of complex cardiac anatomy and sophisticated functional mechanisms compared with conventional 2D echocardiography (2DE), and are comparable to those achieved with magnetic resonance imaging. Many of the limitations associated with the early iterations of 3DE prevented their widespread clinical application. However, recent significant improvements in transducer and post-processing software technologies have addressed many of these issues. Furthermore, the most recent advances in the ability to image the entire heart in realtime and fully automated quantification have poised 3DE to become more ubiquitous in clinical routine. Realtime 3DE (RT3DE) systems offer further improvements in the diagnostic and treatment planning capabilities of cardiac ultrasound. Innovations such as the ability to acquire non-stitched, realtime, full-volume 3D images of the heart in a single heart cycle promise to overcome some of the current limitations of current RT3DE systems, which acquire images over four to seven cardiac cycles, with the need for gating and the potential for stitch artefacts.

Using SurveyMonkey® to teach safe social media strategies to medical students in their clinical years

2015 ◽  
Vol 11 (2) ◽  
pp. 117-124 ◽  
Author(s):  
Katrina A. Bramstedt ◽  
Ben Ierna ◽  
Victoria Woodcroft-Brown
Keyword(s):  
Social Media ◽  
Medical Students ◽  
Media Ethics ◽  
Ethical Awareness ◽  
Media Technology ◽  
Undergraduate Medical Students ◽  
Clinical Rotations ◽  
Medical Apps ◽  
Practice Of Medicine ◽  
Medical Photography

Social media is a valuable tool in the practice of medicine, but it can also be an area of ‘treacherous waters’ for medical students. Those in their upper years of study are off-site and scattered broadly, undertaking clinical rotations; thus, in-house (university lecture) sessions are impractical. Nonetheless, during these clinical years students are generally high users of social media technology, putting them at risk of harm if they lack appropriate ethical awareness. We created a compulsory session in social media ethics (Doctoring and Social Media) offered in two online modes (narrated PowerPoint file or YouTube video) to fourth- and fifth-year undergraduate medical students. The novelty of our work was the use of SurveyMonkey® to deliver the file links, as well as to take attendance and deliver a post-session performance assessment. All 167 students completed the course and provided feedback. Overall, 73% Agreed or Strongly Agreed the course session would aid their professionalism skills and behaviours, and 95% supported delivery of the curriculum online. The most frequent areas of learning occurred in the following topics: email correspondence with patients, medical photography, and awareness of medical apps. SurveyMonkey® is a valuable and efficient tool for curriculum delivery, attendance taking, and assessment activities.

Identification of Chronic Hypersensitivity Pneumonitis Biomarkers with Machine Learning and Differential Co-expression Analysis

2020 ◽  
Vol 20 ◽  
Author(s):  
Hongwei Zhang ◽  
Steven Wang ◽  
Tao Huang
Keyword(s):  
Feature Selection ◽  
Expression Analysis ◽  
Hypersensitivity Pneumonitis ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Great Promise ◽  
Support Vector ◽  
Svm Classifier ◽  
Clinical Tool ◽  
Chronic Hypersensitivity Pneumonitis

Aims: We would like to identify the biomarkers for chronic hypersensitivity pneumonitis (CHP) and facilitate the precise gene therapy of CHP. Background: Chronic hypersensitivity pneumonitis (CHP) is an interstitial lung disease caused by hypersensitive reactions to inhaled antigens. Clinically, the tasks of differentiating between CHP and other interstitial lungs diseases, especially idiopathic pulmonary fibrosis (IPF), were challenging. Objective: In this study, we analyzed the public available gene expression profile of 82 CHP patients, 103 IPF patients, and 103 control samples to identify the CHP biomarkers. Method: The CHP biomarkers were selected with advanced feature selection methods: Monte Carlo Feature Selection (MCFS) and Incremental Feature Selection (IFS). A Support Vector Machine (SVM) classifier was built. Then, we analyzed these CHP biomarkers through functional enrichment analysis and differential co-expression analysis. Result: There were 674 identified CHP biomarkers. The co-expression network of these biomarkers in CHP included more negative regulations and the network structure of CHP was quite different from the network of IPF and control. Conclusion: The SVM classifier may serve as an important clinical tool to address the challenging task of differentiating between CHP and IPF. Many of the biomarker genes on the differential co-expression network showed great promise in revealing the underlying mechanisms of CHP.

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