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 |
347) media were significantly enriched in high-risk individuals. |
348) implant interface in all groups, only low-risk individuals exhibited suppression of |
349) 246 AD risk genes have not been identified as AD |
350) We identified 342 putative AD risk genes in 203 risk regions spanning 50 |
351) for developing therapeutics targeting AD risk genes or risk variants to influence A |
352) -depth functional analyses showed that AD risk genes were overrepresented in AD-rela |
353) erging from the literature, recognises at-risk populations and highlights opportunit |
354) The majority were from low-risk populations. |
355) -2019) acute/early infections in three at risk populations - MSM, high risk women (H |
356) ing in a greater number of vulnerable and risk populations of tuberculosis. |
357) hesized that a population-level polygenic risk score (PRS) can explain phenotypic va |
358) ed the predictive accuracy of a polygenic risk score (PRS) derived from a European a |
359) In the second stage, we use the baseline risk score from the first stage as a singl |
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