ライフサイエンスコーパス: clinical decision making

1 se challenges for diagnosis, treatments, and clinical decision making.

2 radiation and temozolomide and to influence clinical decision making.

3 ue of 0.80 has been widely accepted to guide clinical decision making.

4 lysis of diagnostic studies that will aid in clinical decision making.

5 hting again the importance of genotype-based clinical decision making.

6 weight-loss surgery are available to support clinical decision making.

7 affect disease definitions or contribute to clinical decision making.

8 thostatic HRR predicts mortality and may aid clinical decision making.

9 ow comparisons across trials, and strengthen clinical decision making.

10 th patient values and preferences to improve clinical decision making.

11 nal development of novel immunotherapies and clinical decision making.

12 ity of the appropriate use criteria to guide clinical decision making.

13 he relationship between unconscious bias and clinical decision making.

14 oration of nomogram-derived prognosis to aid clinical decision making.

15 ration of long-term outcome information into clinical decision making.

16 fter an intervention as opposed to improving clinical decision making.

17 tic acute kidney injury could help to inform clinical decision making.

18 are appropriate, and to provide guidance on clinical decision making.

19 hresholds are necessary to facilitate better clinical decision making.

20 classification system that might be used in clinical decision making.

21 It is unknown whether this assay impacts clinical decision making.

22 ease and primary FSGS and may serve to guide clinical decision making.

23 to identify levels that might be valuable in clinical decision making.

24 would increase the information available for clinical decision making.

25 ular and radiologic information for enhanced clinical decision making.

26 nd the potential effect of this reporting on clinical decision making.

27 ic cardiomyopathy , highlighting its role in clinical decision making.

28 g beyond the framework of research to inform clinical decision making.

29 ed by additional testing in order to improve clinical decision making.

30 Ts) to be the strongest form of evidence for clinical decision making.

31 nd the implication of genomic discoveries on clinical decision making.

32 The CT scan findings did not alter clinical decision making.

33 evolve to meet the needs of patient-centered clinical decision making.

34 terpretation and translation of the data for clinical decision making.

35 isk adjustment which may potentially support clinical decision making.

36 ertainty or when the scan will be helpful in clinical decision making.

37 AUC-DST) on rates of appropriate testing and clinical decision making.

38 uccessful application of tumor genotyping in clinical decision making.

39 integration of test results into diagnostic clinical decision making.

40 nical practice to determine prognosis or aid clinical decision making.

41 s expert opinion and clinical data to inform clinical decision making.

42 s to develop a database that can be used for clinical decision making.

43 or infant outcomes to improve counseling and clinical decision making.

44 may lead to bias in research and complicate clinical decision making.

45 ndomized controlled trials are essential for clinical decision making.

46 uitive and may ultimately be used to support clinical decision making.

47 to a validated predictive model to help with clinical decision making.

48 of blood collection, making it available for clinical decision making.

49 scale, which is frequently incompatible with clinical decision making.

50 ieved, potentially providing assistance with clinical decision making.

51 CMV-specific T-cell responses may help guide clinical decision making.

52 breadth of mixed research data is applied to clinical decision making.

53 ss treatment courses on drug development and clinical decision making.

54 ing widespread application of these tests in clinical decision making.

55 implantation and may significantly influence clinical decision making.

56 and to identify risk factors with respect to clinical decision making.

57 discrimination, and hence may be helpful in clinical decision making.

58 patients presenting with LVCM to facilitate clinical decision making.

59 medical education by removing trainees from clinical decision making.

60 s for consideration of general principles of clinical decision making.

61 These 2 predictors should influence clinical decision making.

62 nclature for seizure risk stratification and clinical decision making.

63 ded before they can be used as biomarkers in clinical decision making.

64 y important since data provide the basis for clinical decision making.

65 t-term mortality and might, thus, facilitate clinical decision making.

66 re units and its use has a notable effect on clinical decision making.

67 ility of SCA to have a significant effect on clinical decision making.

68 icting individual ECC outcomes and informing clinical decision making.

69 advance clinical research and better inform clinical decision making.

70 using natural language processing to enrich clinical decision making.

71 l confusion about how to use the results for clinical decision making.

72 of the cardiovascular system are central for clinical decision making.

73 iates in trials to emphasize their impact on clinical decision making.

74 ta confirm that FFR</=0.80 is valid to guide clinical decision making.

75 of 30-day mortality, and ultimately improve clinical decision making.

76 ve disorder (MDD) illness course complicates clinical decision-making.

77 SSI versus risk of AKI is needed to improve clinical decision-making.

78 r system function after stroke could improve clinical decision-making.

79 ential to provide evidence-based data to aid clinical decision-making.

80 e desirable predictive power to be useful in clinical decision-making.

81 ly obtainable risk factors and may assist in clinical decision-making.

82 ving optimal MRA therapy are needed to guide clinical decision-making.

83 come are not precise enough to guide initial clinical decision-making.

84 s could materially influence net effects and clinical decision-making.

85 l's epigenome on a timescale compatible with clinical decision-making.

86 fety of using the sepsis risk model to guide clinical decision-making.

87 These results can inform clinical decision-making.

88 re centers, allow data synthesis, and inform clinical decision-making.

89 on thresholds have been provided to instruct clinical decision-making.

90 ssment of the risk of infection could inform clinical decision-making.

91 iple categories to reflect the complexity of clinical decision-making.

92 can provide objective information to support clinical decision-making.

93 of matched genomic-clinical data can support clinical decision-making.

94 y disorders, with potential implications for clinical decision-making.

95 nhance the role of observational research in clinical decision making: (1) improve the quality of ele

96 rent ability of 'omic' information to inform clinical decision making, (4) emerging ideas about the t

97 cts, nurses' autonomy, scope of practice and clinical decision-making abilities.

98 To improve clinical decision making about management of patients, i

99 for brain damage hampers acute diagnosis and clinical decision making about return to play after spor

100 Both policy-level and clinical decision-making about LDCT screening must consi

101 E risks obtained from this review can aid in clinical decision-making about which people with cancer

102 nd radiographic or ultrasonography changes); clinical decision making (additional testing and pharmac

103 for chronic viral hepatitis C (CHC), shared clinical decision-making addresses the need to engage pa

104 Lyme disease, the C6 EIA could guide initial clinical decision making, although a supplemental immuno

105 G PET/CT may have a significant influence on clinical decision making, although its role is still evo

106 iases were not significantly associated with clinical decision making among acute care surgical clini

107 To perform a clinical decision-making analysis of Sepsis-3 in patient

108 This finding supports clinical decision making and application of biomarkers i

109 is a user-friendly tool that may facilitate clinical decision making and appropriate stratification

110 curate risk-adjustment models are useful for clinical decision making and are important for minimizin

111 stroke and traumatic brain injury to assist clinical decision making and assessing future research d

112 tegration of both comorbidities and age into clinical decision making and comparative-effectiveness r

113 racic magnetic resonance (MR) imaging on the clinical decision making and diagnostic certainty of tho

114 horacic MR imaging substantially affects the clinical decision making and diagnostic certainty of tho

115 gestions provided are intended to facilitate clinical decision making and encourage an evidence-based

116 generating actionable data that will inform clinical decision making and facilitate development of n

117 of different kinds of medical knowledge for clinical decision making and factors beyond study design

118 These associations could guide clinical decision making and further investigations.

119 This observation has the potential to guide clinical decision making and further refine risk stratif

120 ten and are intended to assist physicians in clinical decision making and identify questions and sett

121 ten and are intended to assist physicians in clinical decision making and identify questions and sett

122 that accurately assesses CAS risk could aid clinical decision making and improve patient selection.

123 in systematically applying these findings to clinical decision making and in implementing new technol

124 rious infection in RA patients can influence clinical decision making and inform strategies to reduce

125 anation that will assist clinicians in their clinical decision making and interpretation of troponin

126 Clinical decision making and interprofessional communica

127 ck page cases as a valid construct to assess clinical decision making and interprofessional communica

128 ck page cases as a valid construct to assess clinical decision making and interprofessional communica

129 Clinical decision making and interprofessional communica

130 elcomed the idea of interventions to support clinical decision making and made several proposals towa

131 n occurring after IVTA provides guidance for clinical decision making and management of patients trea

132 gest that unconscious bias may be related to clinical decision making and may predict poor patient-ph

133 s on the implementation of PCR techniques in clinical decision making and on combining them with othe

134 However, its impact on clinical decision making and patient outcome is not full

135 y nonradiologist pediatricians can assist in clinical decision making and procedural success.

136 ltiple risk factors allows for more informed clinical decision making and prognosis at the time of di

137 s appears likely, leading to better-informed clinical decision making and providing insight into dise

138 re (BP) measurements that should be used for clinical decision making and quality reporting are uncer

139 algorithm may prove useful for both bedside clinical decision making and risk adjustment for assessm

140 t compliance with medical therapy may inform clinical decision making and should be incorporated into

141 These results are important for clinical decision making and suggest that adenotonsillec

142 This variability poses challenges for clinical decision making and the development of novel th

143 nical research are slow to have an impact on clinical decision making and thus to benefit patients; 2

144 tic classification, which can in turn inform clinical decision making and treatment matching.

145 Risk stratification is the cornerstone for clinical decision making and treatment selection for the

146 CMML patients, providing a robust basis for clinical decision-making and a reliable tool for clinica

147 Therefore, prognostic tools to guide clinical decision-making and avoid overtreatment of indo

148 for disease progression would be useful for clinical decision-making and designing clinical trials.

149 Frailty and dementia should be considered in clinical decision-making and guideline development.

150 en, and are intended to assist physicians in clinical decision-making and identify questions and sett

151 al pathogens prior to culturing could inform clinical decision-making and improve reaction time.

152 Genetics is already being used to direct clinical decision-making and its contribution is likely

153 ML have significantly improved our tools for clinical decision-making and promise to identify new the

154 f how to best incorporate genomic testing in clinical decision-making and subsequent treatment recomm

155 available molecular markers truly influence clinical decision-making and treatment.

156 These findings raise important questions for clinical decision-making and value-based policy.

157 m development of new diagnostics, facilitate clinical decision making, and improve surveillance for d

158 iew the effects of RAS and BRAF mutations on clinical decision making, and reflect on future directio

159 al role of patient values and preferences in clinical decision making, and the development of the met

160 ires changes in the healthcare system and in clinical decision-making, and early applications of pers

161 Purpose To determine the demographic, clinical, decision-making, and quality-of-life factors t

162 currence of each respective event and inform clinical decision making are lacking.

163 patients in the group in whom challenges in clinical decision making are most prevalent.

164 me endpoints, absolute changes and impact on clinical decision-making are marginal.

165 a triage strategy improved the efficiency of clinical decision making, as compared with a standard ev

166 improve prognostication and, more generally, clinical decision-making because the different driver mu

167 classification system has its limitations in clinical decision making, because it does not adequately

168 to identify high-risk patients and to guide clinical decision making before and after intervention.

169 These risk/benefit data serve as a basis for clinical decision-making before entering an intraportal

170 h tools could improve treatment by informing clinical decision-making before the commencement of trea

171 a biomarker panel could improve the speed of clinical decision-making, both in the treatment of ALI a

172 Non-clinical factors (NCFs) influence clinical decision making but are rarely considered.

173 the condition limits the knowledge base for clinical decision making, but a few published randomised

174 Accounting for them is not only relevant to clinical decision-making, but should also be considered

175 athologic factors and can aid individualized clinical decision making by estimating predicted benefit

176 signaling in a given tumor could help inform clinical decision making by helping guide personalized t

177 This review article seeks to aid clinical decision making by providing an overview of ava

178 ular profiling data has been used to improve clinical decision making by stratifying subjects based o

179 )FP-CIT) in assisting practitioners in their clinical decision making by visualising the dopamine tra

180 and therefore have the potential to advance clinical decision-making by systematically analyzing sta

181 I (aimed at assessing medical knowledge and clinical decision making) can be taken on graduation fro

182 and treatment of breast cancer have made the clinical decision-making context much more complex.

183 However, most ICU clinical decision making continues to take place indepen

184 difficult-to-control asthma is important for clinical decision making, drug development, and reimburs

185 ion of presented results may also facilitate clinical decision making during surgery for large renal

186 gained traction as an important adjunct for clinical decision making during vitreoretinal surgery, a

187 ermining prognosis, although its utility for clinical decision-making entails validation.

188 onal status, with potential implications for clinical decision making, especially within prospective

189 incorporating cardiac magnetic resonance in clinical decision making for defibrillator therapy are w

190 Supporting frontline worker clinical decision making for maternal and newborn servic

191 many aspects and could aid in diagnosis and clinical decision making for patients with acute, acute

192 predictors and may have an ascendant role in clinical decision making for poststroke rehabilitation,

193 ysiology of different TOS subtypes and guide clinical decision making for this disorder.

194 Such insight might be useful in the clinical decision making for those who apply emicizumab

195 al evaluation process, this tool can support clinical decision making for treatment duration.

196 Clinical decision-making for pediatric patients with hea

197 In addition to providing a framework for clinical decision-making, future research strategies wil

198 n 6 US patients undergoing integrase GRT for clinical decision making harbors significant resistance,

199 rder AUC-DST on rates of appropriateness and clinical decision making has not been examined.

200 Incorporating biomarkers into clinical decision making has the potential to more accur

201 role of other forms of medical knowledge for clinical decision making have not been carefully examine

202 These two components of clinical decision making help to explain the so-called s

203 ver metastases would be invaluable to inform clinical decision making; however, deriving this informa

204 y being discussed as critical thresholds for clinical decision making (immediate polypectomy versus p

205 e useful for genetic counseling and may help clinical decision making in a fast and cost-efficient ma

206 function plays an essential role for optimal clinical decision making in a variety of diseases.

207 R values derived from patients with SIHD for clinical decision making in ACS patients.

208 Although FFR is increasingly used for clinical decision making in acute coronary syndrome (ACS

209 aking, which is reflective of the reality of clinical decision making in acute hospital wards.

210 d risk classifications are routinely used in clinical decision making in AML.

211 deep learning aided diagnosis can facilitate clinical decision making in breast cancer by identifying

212 PC3 mutations, there is little data to guide clinical decision making in cases with double mutations.

213 c risk classifications are routinely used in clinical decision making in CLL.

214 k stratification is an integral component of clinical decision making in heart failure (HF).

215 culation ischemic stroke, and it can support clinical decision making in high-risk patients.

216 MTRs can and have been validated for use in clinical decision making in malignant diseases, along wi

217 ere is a pervasive lack of evidence to guide clinical decision making in older patients with cardiova

218 ilor individual treatment regimens and guide clinical decision making in other cancers, these princip

219 iFR cannot be recommended for clinical decision making in patients with coronary arter

220 cal practice for risk-stratification and for clinical decision making in patients with organic MR.

221 8)F-FET PET can add valuable information for clinical decision making in pediatric brain tumor patien

222 Cardiac MR is feasible and may be useful in clinical decision making in pediatric pulmonary hyperten

223 Future studies assessing the role of MRI in clinical decision making in terms of prognostic value fo

224 with FNA cytology plays an integral role in clinical decision making in the management of masses in

225 The model has the potential to facilitate clinical decision making in the staging of NSCLC.

226 day mortality rates should promote review of clinical decision making in these hospitals.

227 These data are potentially important for clinical decision making in this patient population.

228 provides incremental information to improve clinical decision making in women with suspected CAD.

229 add incremental diagnostic value but guides clinical decision-making in an unsalutary fashion.

230 application of ANNs as a tool for assisting clinical decision-making in neurosurgery.

231 ng can identify mutations that could improve clinical decision-making in routine cancer care, potenti

232 al to provide quantitative frameworks to aid clinical decision-making in the treatment of acute strok

233 ibility testing remains a limiting factor in clinical decision-making in the treatment of bacterial i

234 In clinical decision making, in addition to anatomical info

235 To be most useful in clinical decision making, intraparenchymal hemorrhage pr

236 distribution and toxicity in the CNS affect clinical decision making is also debated.

237 oration of observational research as part of clinical decision making is consistent with the position

238 of key evidence-based medicine principles in clinical decision making is fundamental to preventing ov

239 yptococcal meningitis, but its use in aiding clinical decision making is hampered by the time involve

240 into the use of actual blood test values in clinical decision making is required especially as the i

241 rated "systems medicine" approaches in which clinical decision making is supported by statistical and

242 Variation in clinical decision making is, in turn, affected by broad

243 However, clinical decision-making is confounded by the fact that

244 A key factor in clinical decision-making is that patients with mutations

245 assessment and cannot replace fully informed clinical decision making, it is hoped that the screen wi

246 er-eye MD can be more easily integrated into clinical decision-making, making better-eye MD a robust

247 derstanding of how unconscious biases affect clinical decision making may help to illuminate clinicia

248 rate hemodynamic assessment is important for clinical decision-making, O2 should be directly measured

249 prognostically significant and could inform clinical decision making on primary prevention ICD candi

250 n perceptions of neurologic prognosis and in clinical decision making on the level of care was found

251 ry toward the determination of prognosis and clinical decision making on the level of care.

252 implications when these models are used for clinical decision making or to adjust governance analyse

253 rder terms are not sufficiently reliable for clinical decision making or treatment.

254 proved in general for both communication and clinical decision making over the 4-week course.

255 proved in general for both communication and clinical decision making over the 4-week course.

256 literature provide only limited guidance in clinical decision making owing to heterogeneity and scar

257 and its potential power to facilitate better clinical decision making, particularly in the care of pa

258 rediction tools are yet useful for practical clinical decision-making, probably reflecting our limite

259 substitute incorporation is critical in the clinical decision making process and requires special in

260 ation could contribute to improving both the clinical decision-making process in and management of th

261 individual risk estimate contributes to the clinical decision-making process.

262 the value of this on-treatment marker in the clinical decision-making process.

263 tions on how this test should be used in the clinical decision-making process.

264 ntial complementary role in the acute stroke clinical decision-making process.

265 regurgitation (MR) severity is important for clinical decision making, prognostication, and decisions

266 r of bone graft incorporation and can aid in clinical decision making provided standard radiographic

267 bacterial infections, hopefully facilitating clinical decision making regarding further investigation

268 l valve surgery to medical therapy, however, clinical decision making regarding surgery for these fra

269 There is little evidence to guide clinical decision making regarding the use of prasugrel

270 However, limited evidence exists to aid clinical decision making regarding which patients will b

271 importance of SVT and may form the basis for clinical decision-making regarding anticoagulation.

272 ation to the histological classification and clinical decision-making related to early disease.

273 Clinical decision making relative to community-acquired

274 Counseling and clinical decision making should acknowledge these correl

275 ho diagnose and manage Kawasaki disease, but clinical decision making should be individualized to spe

276 aggressiveness with the potential to impact clinical decision-making, such as targeted biopsy approa

277 r patient engagement, the development of new clinical decision-making support tools, and the validati

278 based discovery in biomedicine as well as in clinical decision-making support.

279 d scales offer a potentially useful tool for clinical decision-making, tailoring treatment to patient

280 a conceptual model of the process of shared clinical decision making that involves four stepped leve

281 not replicate; 4) when the results influence clinical decision making, the results clinicians obtain

282 Clinical decision making therefore requires individualiz

283 nd treatment efficacy predictions for better clinical decision making through large volume of data.

284 ) data are available, and they actively help clinical decision-making through the assessment of wheth

285 Incorporation of biomarkers into clinical decision making to define therapeutic managemen

286 iving anticoagulation, is used to illustrate clinical decision making to determine ongoing treatment.

287 f hemodynamics may serve as a supplement for clinical decision-making to prevent the occurrence of a

288 To our knowledge, this is the first clinical decision-making tool that generates personalize

289 apeutic approaches play an important role in clinical decision making, treatment guidelines, and heal

290 ablished tools for diagnosis, prognosis, and clinical decision making, understanding the advantages a

291 To help guide individualized clinical decision making, we compared HRQOL among patien

292 To assist clinical decision making, we pooled the existing evidenc

293 osis factor agents and thiopurines to inform clinical decision making when applying TDM in a reactive

294 The results of this study will aid clinical decision making when choosing biologic therapy

295 The results of this study should support clinical decision making when choosing second-line biolo

296 ng because these are variables that may help clinical decision making when multiple potential donors

297 More accurate AKI risk estimates may improve clinical decision-making when attempting to balance the

298 Although clinical decision-making will be guided mainly by clinic

299 on is commonly used but infrequently impacts clinical decision making with major financial burden.

300 ery by nearly one-third and could help guide clinical decision making with regard to surveillance ver