scholarly journals Reliability and Variability Assessment of Femoral Artery Pseudoaneurysm Measurements Between Pre- and Postprocessed B-mode Ultrasound Images

2020 ◽  
Vol 36 (3) ◽  
pp. 212-222
Author(s):  
Reham Kaifi ◽  
Mohammed Almatrafi ◽  
Ferdos Alahmary ◽  
Andrew Chen ◽  
Robyn Macsata ◽  
...  
Keyword(s):  
Image Processing ◽  
Femoral Artery ◽  
Medical Center ◽  
Intraclass Correlation ◽  
The United States ◽  
Ultrasound Images ◽  
Neck Length ◽  
Artery Pseudoaneurysm ◽  
Neck Width ◽  
Major Medical Center

Objective: To assess the reliability and variability of femoral artery pseudoaneurysm (FAP) measurements between pre- and postprocessed sonograms acquired in a major medical center in Saudi Arabia as compared with results obtained from a major medical center in the United States. Methods: Retrospective image analysis was conducted on 23 FAP sonograms, which were evaluated by four observers. Observers measured FAP sac and neck from pre- and postprocessed images and remeasured again after 2 weeks, to avoid recall bias. Results: The use of image processing was more profound for the novice observers in measuring FAP neck width and length. The intraclass correlation coefficient (ICC) for FAP neck width improved after segmentation from 0.63 to 0.91; in contrast, the ICC improved from 0.91 to 0.97 for experts. The average ICCs for FAP neck length improved from 0.40 to 0.79 for novices and from 0.86 to 0.95 for experts. The largest variation of values, within observers, were for neck length obtained from the original images. The range varied from 0.16 to 0.37 cm and was reduced to 0.10 to 0.18 cm with segmented images. Conclusion: As demonstrated previously, sonographic image processing resulted in increased reliability and decreased variability for FAP measurements.

scholarly journals Intra- and Interobserver Reliability and Variability of Femoral Artery Pseudoaneurysm Measurements Between Pre- and Postprocessed B-mode Sonographic Images

2018 ◽  
Vol 35 (2) ◽  
pp. 87-94 ◽  
Author(s):  
Reham Kaifi ◽  
Lauren Price ◽  
Andrew Chen ◽  
Babak Sarani ◽  
Vesna Zderic
Keyword(s):  
Femoral Artery ◽  
Interobserver Variability ◽  
Interobserver Reliability ◽  
Intraclass Correlation ◽  
Region Of Interest ◽  
Body Width ◽  
Artery Pseudoaneurysm ◽  
Neck Width ◽  
Contrast Enhanced ◽  
Trained Observers

The objective was to enhance the contrast and segment the femoral artery pseudoaneurysm (FAP) area from patients’ ultrasonography (US) images. In addition, this study compared the intra- and interobserver reliability and variability of the FAP measurements from the original, contrast-enhanced, and segmented US. Retrospectively, 25 FAP sonograms were evaluated by four observers (two trained and two novice). They twice measured the FAP body width, neck width, and length from original, enhanced, and segmented US. The intra- and interobserver reliability for measuring FAP body width, neck width, and neck length improved by 10% after enhancing the original 2D US contrast and segmenting the region of interest across all observers. Also, the intra- and interobserver variability among measurements across all observers decreased by 44%. Using US processing was more profound for novice observers (intraclass correlation coefficient [ICC], 0.76–0.93) compared to trained observers (ICC, 0.94–0.99). US postprocessing resulted in a decrease in variability for FAP measurements.

A Database for Counterfeit Electronics and Automatic Defect Detection Based on Image Processing and Machine Learning

2016 ◽  
Author(s):  
Navid Asadizanjani ◽  
Sachin Gattigowda ◽  
Mark Tehranipoor ◽  
Domenic Forte ◽  
Nathan Dunn
Keyword(s):  
Machine Learning ◽  
Image Processing ◽  
Integrated Circuits ◽  
Web Application ◽  
The United States ◽  
Global Market ◽  
Online Database ◽  
Ongoing Effort ◽  
Time Period ◽  
Physical Defects

Abstract Counterfeiting is an increasing concern for businesses and governments as greater numbers of counterfeit integrated circuits (IC) infiltrate the global market. There is an ongoing effort in experimental and national labs inside the United States to detect and prevent such counterfeits in the most efficient time period. However, there is still a missing piece to automatically detect and properly keep record of detected counterfeit ICs. Here, we introduce a web application database that allows users to share previous examples of counterfeits through an online database and to obtain statistics regarding the prevalence of known defects. We also investigate automated techniques based on image processing and machine learning to detect different physical defects and to determine whether or not an IC is counterfeit.

Ultrasound-guided compression of femoral artery pseudoaneurysm

1992 ◽  
Vol 11 (4) ◽  
pp. 182-183 ◽  
Author(s):  
M Shapiro ◽  
H L Cohen ◽  
K Crystal ◽  
D Katz
Keyword(s):  
Femoral Artery ◽  
Ultrasound Guided ◽  
Artery Pseudoaneurysm

scholarly journals The COVID Army: Experiences from the Deployment of Non-Hospitalist Physician Volunteers during the 2020 COVID Pandemic

2021 ◽  
pp. 1-15
Author(s):  
Kevin Hauck ◽  
Katherine Hochman ◽  
Mark Pochapin ◽  
Sondra Zabar ◽  
Jeffrey A Wilhite ◽  
...  
Keyword(s):  
New York ◽  
New York City ◽  
Medical Center ◽  
The United States ◽  
Lessons Learned ◽  
Front Line ◽  
Clinical Leadership ◽  
Team Members ◽  
Medical Centers ◽  
Hospitalist Physician

Abstract Objective New York City was the epicenter of the outbreak of the 2020 COVID-19 pandemic in the United States. As a large, quaternary care medical center, NYU Langone Medical Center was one of many New York medical centers that experienced an unprecedented influx of patients during this time. Clinical leadership effectively identified, oriented, and rapidly deployed a “COVID Army”, consisting of non-hospitalist physicians, to meet the needs of this patient influx. We share feedback from our providers on our processes and offer specific recommendations for systems experiencing a similar influx in the current and future pandemics. Methods In order to assess the experiences and perceived readiness of these physicians (n=183), we distributed a 32-item survey between March and June of 2020. Thematic analyses and response rates were examined in order to develop results. Results Responses highlighted varying experiences and attitudes of our front-line physicians during an emerging pandemic. Thematic analyses revealed a series of lessons learned, including the need to: (1) provide orientations, (2) clarify roles/ workflow, (3) balance team workload, (4) keep teams updated on evolving policies, (5) make team members feel valued, and (6) ensure they have necessary tools available. Conclusions Lessons from our deployment and assessment are scalable at other institutions.

scholarly journals Perinatal Mood and Anxiety Disorder Management in Multicenter Community Practices: Clinicians’ Training, Current Practices and Perceived Strategies to Improve Future Implementation

2021 ◽  
Vol 12 ◽  
pp. 215013272199688
Author(s):  
Ajeng J. Puspitasari ◽  
Dagoberto Heredia ◽  
Elise Weber ◽  
Hannah K Betcher ◽  
Brandon J. Coombes ◽  
...  
Keyword(s):  
Anxiety Disorder ◽  
Health Services ◽  
Behavioral Health ◽  
Psychiatric Symptoms ◽  
Medical Center ◽  
Academic Medical Center ◽  
Management Training ◽  
The United States ◽  
Behavioral Health Services ◽  
Perinatal Women

Background: This study aimed to explore clinicians’ perspectives on the current practice of perinatal mood and anxiety disorder (PMAD) management and strategies to improve future implementation. Methods: This study had a cross-sectional, descriptive design. A 35-item electronic survey was sent to clinicians (N = 118) who treated perinatal women and practiced at several community clinics at an academic medical center in the United States. Results: Among clinicians who provided care for perinatal women, 34.7% reported never receiving PMAD management training and 66.3% had less than 10 years of experience. Out of 10 patients who reported psychiatric symptoms, 47.8% of clinicians on average reported providing PMAD management to 1 to 3 patients and 40.7% noted that they conducted screening only when patient expresses PMAD symptoms. Suggested future improvements were providing training, developing a referral list, and establishing integrated behavioral health services. Conclusions: Results from this study indicated that while PMAD screening and management was implemented, improvements are warranted to meet established guidelines. Additionally, clinicians endorsed providing PMAD management to a small percentage of perinatal patients. Suggested strategies to increase adoption and implementation of PMAD management should be explored to improve access to behavioral health services for perinatal women.

scholarly journals Patient-Specific Predictive Antibiogram in Decision Support for Empiric Antibiotic Treatment

2020 ◽  
Vol 41 (S1) ◽  
pp. s521-s522
Author(s):  
Debarka Sengupta ◽  
Vaibhav Singh ◽  
Seema Singh ◽  
Dinesh Tewari ◽  
Mudit Kapoor ◽  
...  
Keyword(s):  
Machine Learning ◽  
Antimicrobial Resistance ◽  
Model Building ◽  
Medical Center ◽  
Bacterial Species ◽  
Model Performance ◽  
The United States ◽  
Patient Specific ◽  
Gradient Boosting ◽  
Comparative Performance

Background: The rising trend of antibiotic resistance imposes a heavy burden on healthcare both clinically and economically (US$55 billion), with 23,000 estimated annual deaths in the United States as well as increased length of stay and morbidity. Machine-learning–based methods have, of late, been used for leveraging patient’s clinical history and demographic information to predict antimicrobial resistance. We developed a machine-learning model ensemble that maximizes the accuracy of such a drug-sensitivity versus resistivity classification system compared to the existing best-practice methods. Methods: We first performed a comprehensive analysis of the association between infecting bacterial species and patient factors, including patient demographics, comorbidities, and certain healthcare-specific features. We leveraged the predictable nature of these complex associations to infer patient-specific antibiotic sensitivities. Various base-learners, including k-NN (k-nearest neighbors) and gradient boosting machine (GBM), were used to train an ensemble model for confident prediction of antimicrobial susceptibilities. Base learner selection and model performance evaluation was performed carefully using a variety of standard metrics, namely accuracy, precision, recall, F1 score, and Cohen κ. Results: For validating the performance on MIMIC-III database harboring deidentified clinical data of 53,423 distinct patient admissions between 2001 and 2012, in the intensive care units (ICUs) of the Beth Israel Deaconess Medical Center in Boston, Massachusetts. From ~11,000 positive cultures, we used 4 major specimen types namely urine, sputum, blood, and pus swab for evaluation of the model performance. Figure 1 shows the receiver operating characteristic (ROC) curves obtained for bloodstream infection cases upon model building and prediction on 70:30 split of the data. We received area under the curve (AUC) values of 0.88, 0.92, 0.92, and 0.94 for urine, sputum, blood, and pus swab samples, respectively. Figure 2 shows the comparative performance of our proposed method as well as some off-the-shelf classification algorithms. Conclusions: Highly accurate, patient-specific predictive antibiogram (PSPA) data can aid clinicians significantly in antibiotic recommendation in ICU, thereby accelerating patient recovery and curbing antimicrobial resistance.Funding: This study was supported by Circle of Life Healthcare Pvt. Ltd.Disclosures: None

scholarly journals Communications and Screening for 2019 Novel Coronavirus at a Tertiary-Care Medical Center

2020 ◽  
Vol 41 (S1) ◽  
pp. s84-s84
Author(s):  
Lorinda Sheeler ◽  
Mary Kukla ◽  
Oluchi Abosi ◽  
Holly Meacham ◽  
Stephanie Holley ◽  
...  
Keyword(s):  
Screening Tool ◽  
Medical Center ◽  
Academic Medical Center ◽  
Tertiary Care ◽  
The United States ◽  
World Health ◽  
Communication Campaign ◽  
Electronic Screening ◽  
Novel Coronavirus ◽  
The Impact

Background: In December of 2019, the World Health Organization reported a novel coronavirus (severe acute respiratory coronavirus virus 2 [SARS-CoV-2)]) causing severe respiratory illness originating in Wuhan, China. Since then, an increasing number of cases and the confirmation of human-to-human transmission has led to the need to develop a communication campaign at our institution. We describe the impact of the communication campaign on the number of calls received and describe patterns of calls during the early stages of our response to this emerging infection. Methods: The University of Iowa Hospitals & Clinics is an 811-bed academic medical center with >200 outpatient clinics. In response to the coronavirus disease 2019 (COVID-19) outbreak, we launched a communications campaign on January 17, 2020. Initial communications included email updates to staff and a dedicated COVID-19 webpage with up-to-date information. Subsequently, we developed an electronic screening tool to guide a risk assessment during patient check in. The screening tool identifies travel to China in the past 14 days and the presence of symptoms defined as fever >37.7°C plus cough or difficulty breathing. The screening tool was activated on January 24, 2020. In addition, university staff contacted each student whose primary residence record included Hubei Province, China. Students were provided with medical contact information, signs and symptoms to monitor for, and a thermometer. Results: During the first 5 days of the campaign, 3 calls were related to COVID-19. The number of calls increased to 18 in the 5 days following the implementation of the electronic screening tool. Of the 21 calls received to date, 8 calls (38%) were generated due to the electronic travel screen, 4 calls (19%) were due to a positive coronavirus result in a multiplex respiratory panel, 4 calls (19%) were related to provider assessment only (without an electronic screening trigger), and 2 calls (10%) sought additional information following the viewing of the web-based communication campaign. Moreover, 3 calls (14%) were for people without travel history but with respiratory symptoms and contact with a person with recent travel to China. Among those reporting symptoms after travel to China, mean time since arrival to the United States was 2.7 days (range, 0–11 days). Conclusion: The COVID-19 outbreak is evolving, and providing up to date information is challenging. Implementing an electronic screening tool helped providers assess patients and direct questions to infection prevention professionals. Analyzing the types of calls received helped tailor messaging to frontline staff.Funding: NoneDisclosures: None

scholarly journals Testing telediagnostic obstetric ultrasound in Peru: a new horizon in expanding access to prenatal ultrasound

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Marika Toscano ◽  
Thomas J. Marini ◽  
Kathryn Drennan ◽  
Timothy M. Baran ◽  
Jonah Kan ◽  
...  
Keyword(s):  
Excellent Agreement ◽  
Rural Areas ◽  
Intraclass Correlation ◽  
Standard Of Care ◽  
The United States ◽  
Categorical Variables ◽  
Continuous Variables ◽  
Second Trimester ◽  
Obstetric Ultrasound ◽  
Biometric Measurements

Abstract Background Ninety-four percent of all maternal deaths occur in low- and middle-income countries, and the majority are preventable. Access to quality Obstetric ultrasound can identify some complications leading to maternal and neonatal/perinatal mortality or morbidity and may allow timely referral to higher-resource centers. However, there are significant global inequalities in access to imaging and many challenges to deploying ultrasound to rural areas. In this study, we tested a novel, innovative Obstetric telediagnostic ultrasound system in which the imaging acquisitions are obtained by an operator without prior ultrasound experience using simple scan protocols based only on external body landmarks and uploaded using low-bandwidth internet for asynchronous remote interpretation by an off-site specialist. Methods This is a single-center pilot study. A nurse and care technician underwent 8 h of training on the telediagnostic system. Subsequently, 126 patients (68 second trimester and 58 third trimester) were recruited at a health center in Lima, Peru and scanned by these ultrasound-naïve operators. The imaging acquisitions were uploaded by the telemedicine platform and interpreted remotely in the United States. Comparison of telediagnostic imaging was made to a concurrently performed standard of care ultrasound obtained and interpreted by an experienced attending radiologist. Cohen’s Kappa was used to test agreement between categorical variables. Intraclass correlation and Bland-Altman plots were used to test agreement between continuous variables. Results Obstetric ultrasound telediagnosis showed excellent agreement with standard of care ultrasound allowing the identification of number of fetuses (100% agreement), fetal presentation (95.8% agreement, κ =0.78 (p < 0.0001)), placental location (85.6% agreement, κ =0.74 (p < 0.0001)), and assessment of normal/abnormal amniotic fluid volume (99.2% agreement) with sensitivity and specificity > 95% for all variables. Intraclass correlation was good or excellent for all fetal biometric measurements (0.81–0.95). The majority (88.5%) of second trimester ultrasound exam biometry measurements produced dating within 14 days of standard of care ultrasound. Conclusion This Obstetric ultrasound telediagnostic system is a promising means to increase access to diagnostic Obstetric ultrasound in low-resource settings. The telediagnostic system demonstrated excellent agreement with standard of care ultrasound. Fetal biometric measurements were acceptable for use in the detection of gross discrepancies in fetal size requiring further follow up.

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