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Sökning: WFRF:(Mortazavi S. M. J.)

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  • Ash, G. I., et al. (författare)
  • Establishing a Global Standard for Wearable Devices in Sport and Exercise Medicine: Perspectives from Academic and Industry Stakeholders
  • 2021
  • Ingår i: Sports Medicine. - : Springer Science and Business Media LLC. - 0112-1642 .- 1179-2035. ; 51, s. 2237-2250
  • Tidskriftsartikel (refereegranskat)abstract
    • Millions of consumer sport and fitness wearables (CSFWs) are used worldwide, and millions of datapoints are generated by each device. Moreover, these numbers are rapidly growing, and they contain a heterogeneity of devices, data types, and contexts for data collection. Companies and consumers would benefit from guiding standards on device quality and data formats. To address this growing need, we convened a virtual panel of industry and academic stakeholders, and this manuscript summarizes the outcomes of the discussion. Our objectives were to identify (1) key facilitators of and barriers to participation by CSFW manufacturers in guiding standards and (2) stakeholder priorities. The venues were the Yale Center for Biomedical Data Science Digital Health Monthly Seminar Series (62 participants) and the New England Chapter of the American College of Sports Medicine Annual Meeting (59 participants). In the discussion, stakeholders outlined both facilitators of (e.g., commercial return on investment in device quality, lucrative research partnerships, and transparent and multilevel evaluation of device quality) and barriers (e.g., competitive advantage conflict, lack of flexibility in previously developed devices) to participation in guiding standards. There was general agreement to adopt Keadle et al.'s standard pathway for testing devices (i.e., benchtop, laboratory, field-based, implementation) without consensus on the prioritization of these steps. Overall, there was enthusiasm not to add prescriptive or regulatory steps, but instead create a networking hub that connects companies to consumers and researchers for flexible guidance navigating the heterogeneity, multi-tiered development, dynamicity, and nebulousness of the CSFW field.
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  • Smith, P B, et al. (författare)
  • Cultural values, sources of guidance, and their relevance to managerial behavior - A 47-nation study
  • 2002
  • Ingår i: Journal of Cross-Cultural Psychology. - : Sage Publications. - 0022-0221 .- 1552-5422. ; 33:2, s. 188-208
  • Tidskriftsartikel (refereegranskat)abstract
    • Data are presented showing how middle managers in 47 countries report handling eight specific work events. The data are used to test the ability of cultural value dimensions derived from the work of Hofstede. Trompenaars, and Schwartz to predict the specific sources of guidance on which managers rely. Focusing on sources of guidance is expected to provide a more precise basis than do generalized measures of values for understanding the behaviors that prevail within different cultures. Values are strongly predictive of reliance on those sources of guidance that are relevant to vertical relationships within organizations. Hock ever, values are less successful in predicting reliance on peers and on more tacit sources of guidance. Explaining national differences in these neglected aspects of organizational processes will require greater sensitivity to the culture-specific contexts within which they occur.
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  • Mortazavi, S. M. J., et al. (författare)
  • Does Exposure of Astronauts' Brains to High-LET Radiation in Deep Space Threaten the Success of the Mission?
  • 2020
  • Ingår i: 2020 IEEE AEROSPACE CONFERENCE (AEROCONF 2020). - 1095-323X. - 9781728127347
  • Konferensbidrag (refereegranskat)abstract
    • Astronauts' exposure to radiation is different from exposure to radiation on Earth. Besides cancer, cardiovascular disease and acute radiation syndrome, there are concerns over the potential behavioral and cognitive impairments caused by exposure of the astronauts' central nervous system to high levels of space radiation. Therefore, potential behavioral and cognitive i mpairments caused by astronauts' brains exposure to high levels of space radiation and the possibility of developing dementia and other motor neuron diseases are getting more attention. As NASA is interested in studies on radium deposition in human brain, and exposure of the brain to high linear energy transfer (LET) alpha particles, we have assessed the cognitive effects of long-term exposure of human brain to alpha particles which partly mimics astronauts' exposure to high charge and energy (HZE) particles during upcoming mars missions. Dr. John Boice, President of NCRP, and his colleagues' have stated that human brain exposed for years to alpha particles on Earth may be more relevant to a Mars mission in contrast with the mouse brain exposed to heavy ions for a few minutes. Interestingly, both Boice and NASA did not pay enough attention to this fact that radium as well as many other alpha emitters tend to accumulate in the bone, and the alpha particles whose energies are typically -5 MeV have a very short range (maximum lOs of um), so the radiation dose due to the alpha emitters would be localized to volumes near the cranium rather than being uniformly distributed throughout the cerebral and cerebellar parenchyma. Extraordinary high levels of Ra-226 have previously been reported in high background radiation areas of Ramsar, where people are consuming locally grown foods. In this paper, we will present data which provide a human brain radiation exposure analogue for upcoming Mars missions. Normally the dose to the functional parts of the brain are not likely to be significant, even with higher uptakes of the radium or other alpha-emitting isotopes in the cranium. Therefore, only residents with calcium-rich diet were selected for the study. Measurements of background gamma radiation was performed in their bedrooms, dining rooms, vegetable yards and gardens with citrus fruit trees of the dwellings in areas with high levels of Ra-226 in the soil and at a nearby control area with the same socio-economic factors. Moreover, the food frequency, reaction time, working memory and computational abilities as well as the Radium Ingestion Index (RII) of 47 participants (22 males and 24 females) from the hot areas, where the annual radiation absorbed dose from background radiation is up to 260 mSv/y, were studied, and the same things were studied for 17 participants (4 males and 13 females) from a nearby normal background radiation area with the same socioeconomic factors as at the hot areas. Our study showed that exposure of human brain to high LET particles did not affect the working memory. However, individuals with higher levels of radium ingestion had significantly increased reaction times. The increased reaction time in individuals with higher exposure levels to alpha particles emitted from ingested Ra-226 is an important finding, since similar conditions might occur in deep space, when astronauts' brain cells are exposed to HZE particles. As the astronauts face numerous challenges in isolated and confined space environment, they should be able to respond quickly to different hazards. However, further studies are needed to verify if the fmdings in high radiation dose areas in Ramsar are relevant for deep space mission.
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  • Sangha, Veer, et al. (författare)
  • Detection of Left Ventricular Systolic Dysfunction From Electrocardiographic Images
  • 2023
  • Ingår i: Circulation. - : Wolters Kluwer. - 0009-7322 .- 1524-4539. ; 148:9, s. 765-777
  • Tidskriftsartikel (refereegranskat)abstract
    • BACKGROUND: Left ventricular (LV) systolic dysfunction is associated with a >8-fold increased risk of heart failure and a 2-fold risk of premature death. The use of ECG signals in screening for LV systolic dysfunction is limited by their availability to clinicians. We developed a novel deep learning-based approach that can use ECG images for the screening of LV systolic dysfunction.METHODS: Using 12-lead ECGs plotted in multiple different formats, and corresponding echocardiographic data recorded within 15 days from the Yale New Haven Hospital between 2015 and 2021, we developed a convolutional neural network algorithm to detect an LV ejection fraction <40%. The model was validated within clinical settings at Yale New Haven Hospital and externally on ECG images from Cedars Sinai Medical Center in Los Angeles, CA; Lake Regional Hospital in Osage Beach, MO; Memorial Hermann Southeast Hospital in Houston, TX; and Methodist Cardiology Clinic of San Antonio, TX. In addition, it was validated in the prospective Brazilian Longitudinal Study of Adult Health. Gradient-weighted class activation mapping was used to localize class-discriminating signals on ECG images.RESULTS: Overall, 385 601 ECGs with paired echocardiograms were used for model development. The model demonstrated high discrimination across various ECG image formats and calibrations in internal validation (area under receiving operation characteristics [AUROCs], 0.91; area under precision-recall curve [AUPRC], 0.55); and external sets of ECG images from Cedars Sinai (AUROC, 0.90 and AUPRC, 0.53), outpatient Yale New Haven Hospital clinics (AUROC, 0.94 and AUPRC, 0.77), Lake Regional Hospital (AUROC, 0.90 and AUPRC, 0.88), Memorial Hermann Southeast Hospital (AUROC, 0.91 and AUPRC 0.88), Methodist Cardiology Clinic (AUROC, 0.90 and AUPRC, 0.74), and Brazilian Longitudinal Study of Adult Health cohort (AUROC, 0.95 and AUPRC, 0.45). An ECG suggestive of LV systolic dysfunction portended >27-fold higher odds of LV systolic dysfunction on transthoracic echocardiogram (odds ratio, 27.5 [95% CI, 22.3-33.9] in the held-out set). Class-discriminative patterns localized to the anterior and anteroseptal leads (V2 and V3), corresponding to the left ventricle regardless of the ECG layout. A positive ECG screen in individuals with an LV ejection fraction & GE;40% at the time of initial assessment was associated with a 3.9-fold increased risk of developing incident LV systolic dysfunction in the future (hazard ratio, 3.9 [95% CI, 3.3-4.7]; median follow-up, 3.2 years).CONCLUSIONS: We developed and externally validated a deep learning model that identifies LV systolic dysfunction from ECG images. This approach represents an automated and accessible screening strategy for LV systolic dysfunction, particularly in low-resource settings.
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