314) e suggests that a large proportion of GDM risk in women may be preventable by lifest |
315) racteristics indicative of cardiovascular risk in young males (aged 18 to 30 years |
316) Risk perception varied geographically alon |
317) al, and social drivers of population heat risk perception and how they interact to i |
318) research demonstrates a link between heat risk perception and population response to |
319) lished up to March 2020 and investigating risk perception determinants for respirato |
320) A miscellaneous operationalization of risk perception emerged, including the lik |
321) Understanding the determinants of risk perception for COVID-19 might help to |
322) evidence on the possible determinants of risk perception for COVID-like diseases. |
323) Results revealed risk perception influences a person's expo |
324) mptoms, fatigue, daily activities, stroke risk factors, and cognitive exertion. |
325) ead to better health care outcomes, lower risk factors, and improved interventions r |
326) odemographic correlates, associations, or risk factors, and nine studies examined me |
327) Prognosis/ risk factors, epidemiology, and coagulatio |
328) Establishing risk factors, examining sex differences an |
329) e captured detailed data on demographics, risk factors, pre-COVID-19 Rockwood frailt |
330) addressed prevalence, severity, etiology, risk factors, preventive methods, screenin |
331) ized approaches for smoking cessation and risk prediction for tobacco-related diseas |
332) survival when incorporated into existing risk prediction models. |
333) ncorporating endostatin into existing PAH risk prediction models. |
334) Adding endostatin to existing PAH risk prediction strategies improves PAH ri |
335) mpared to null models based on the REVEAL risk prediction tool and European Society |
336) calibration examining the reliability in risk prediction was performed using either |
337) rvations and the implications for genetic risk prediction. |
338) ersely associated with a pediatric asthma risk stratification based on multiple peri |
339) nfirm causality, use of this finding as a risk stratification biomarker is promising |
340) tatus could be utilized as a predictor of risk stratification for recurrence and to |
341) tokine biomarker signatures might improve risk stratification in LTBI. |
342) Accurate detection and risk stratification of latent tuberculosis |
343) by these characteristics could facilitate risk stratification or new therapeutic tar |
344) dementia screening battery to identify at-risk individuals with DS in primary care s |
345) s of the disease, as well as detecting at-risk individuals. |
346) ' S309-CAR-NK cells for treatment in high-risk individuals as well as provide an alt |
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