ライフサイエンスコーパス: radiologist

1 Disagreements were adjudicated by a third radiologist.

2 formed at the discretion of the interpreting radiologist.

3 abbreviated and full) was made by an expert radiologist.

4 % (95% CI 67%-90%) in standard CT by primary radiologist.

5 y consensus discussion with a third thoracic radiologist.

6 is obtained and when it is interpreted by a radiologist.

7 erpretation by a cardiovascular subspecialty radiologist.

8 sensitivity as compared to a senior thoracic radiologist.

9 enced and blinded, board-certified abdominal radiologist.

10 ogists and exceeded that of less-specialized radiologists.

11 the CV19-Net and three experienced thoracic radiologists.

12 excellent interrater agreement compared with radiologists.

13 ere 10 090 body CT studies interpreted by 32 radiologists.

14 od is a challenge for both gynecologists and radiologists.

15 lthy cervix and the agreement levels between radiologists.

16 compared with adenomas when assessed by both radiologists.

17 AUC of 0.85 (95% CI: 0.81, 0.88) achieved by radiologists.

18 ely, for the same patency gain compared with radiologists.

19 e its performance to that of attending-level radiologists.

20 ve resulted in confusion from clinicians and radiologists.

21 with consensus categorical assessment by two radiologists.

22 ospectively evaluated by two musculoskeletal radiologists.

23 rential diagnoses at brain MRI compared with radiologists.

24 he reliability and agreement between the two radiologists.

25 scle (LHG) and adductor magnus tendon by two radiologists.

26 ical practice to assist neuro-oncologists or radiologists.

27 ations were retrospectively evaluated by two radiologists.

28 mance exceeding that of experienced thoracic radiologists.

29 compared with reference measurements by two radiologists.

30 et by the consensus of two other independent radiologists.

31 in classification between TA and experienced radiologists.

32 lso of relevance to general neurologists and radiologists.

33 informative for the professional training of radiologists.

34 d, randomized, and scored independently by 2 radiologists.

35 g tumor-were manually labeled by experienced radiologists.

36 omments for electroradiology technicians and radiologists.

37 es were identified by two nonreader thoracic radiologists.

38 rity of participants, even by trained breast radiologists.

39 s for GPDL-BAAM (P = .0005), 14.6 months for radiologist 1 (P < .0001), and 16.0 for radiologist 2 (P

40 th 91.6% for GPDL-BAAM (P = .096), 86.0% for radiologist 1 (P < .0001), and 84.6% for radiologist 2 (

41 as 0.83 versus 0.86 and 0.86 versus 0.91 for radiologist 1 and 2, respectively.

42 Subjectively, T2-weighted SI (P < .001 for radiologist 1 and radiologist 2) and T2-weighted heterog

43 Two blinded radiologists (radiologist 1 and radiologist 2) assessed T2-weighted SI

44 and T2-weighted heterogeneity (P < .001, for radiologist 1 and radiologist 2) were higher in metastas

45 (GPDL-BAAM) and two pediatric radiologists (radiologists 1 and 2) using the GP method.

46 for radiologist 1 (P < .0001), and 16.0 for radiologist 2 (P < .0001).

47 for radiologist 1 (P < .0001), and 84.6% for radiologist 2 (P < .0001).

48 -weighted SI (P < .001 for radiologist 1 and radiologist 2) and T2-weighted heterogeneity (P < .001,

49 Two blinded radiologists (radiologist 1 and radiologist 2) assessed T2-weighted SI and T2-weighted h

50 terogeneity (P < .001, for radiologist 1 and radiologist 2) were higher in metastases compared with a

51 ersus 0.58 and 0.39 versus 0.70 (P < .05 for radiologist 2).

52 radiology residents (56%; P < .001), general radiologists (57%; P < .001), and neuroradiology fellows

53 nificantly higher sensitivity (71%) than one radiologist (60%, P < .001) and significantly higher spe

54 nificantly higher specificity (92%) than two radiologists (75%, P < .001; 84%, P = .009).

55 ange, 76%-81%) and the consensus of all five radiologists (81%).

56 year of patency were as follows: $71 000 for radiologists, $89 000 for nephrologists, and $174 000 fo

57 Regarding pneumonia detection, radiologists achieved a maximum diagnostic accuracy of u

58 Reference standards were defined by radiologist-adjudicated image review.

59 Radiologist-adjudicated labels for 2412 ChestX-ray14 val

60 for chest radiograph interpretation by using radiologist-adjudicated reference standards.Materials an

61 st double reading and 85 by the coordinating radiologists after quality assurance sessions.

62 e model was tested against 3 blinded general radiologists and 1 blinded subspecialist using a held-ou

63 estigated by comparing the performance of 10 radiologists and 2 groups of novices on the ability to d

64 by 9 readers (6 fellowship trained thoracic radiologists and 3 radiology resident trainees).

65 A total of 117 volunteer participants (55 radiologists and 62 nonradiologists) took part in a stud

66 ely and independently evaluated by two chest radiologists and a 5th-year radiology resident using the

67 lass correlation coefficients (ICCs) for the radiologists and artificial intelligence (AI) system wer

68 nd intra-observer agreement for the group of radiologists and between the commercial software and the

69 ir relations with the brain is important for radiologists and clinicians evaluating the cerebellum an

70 The difference in thresholds between the radiologists and control groups suggests that experience

71 d fracture dislocation were evaluated by two radiologists and correlated with nerve impairment.

72 lesion-level sensitivity compared to that of radiologists and expert neurosurgeons.

73 e provided to aid both expert and non-expert radiologists and neurologists who may encounter patients

74 Examinations were reviewed by radiologists and nuclear medicine physicians in consensu

75 cores independently assigned by two thoracic radiologists and one in-training radiologist (Pearson r)

76 Materials and Methods Two radiologists and one radiology resident retrospectively

77 roups of human observers: fellowship-trained radiologists and orthopedists; senior residents in emerg

78 Independent radiologists and pathologists assessed the MRI and histo

79 Radiologists and pathologists help play an important rol

80 Board-certified radiologists and pathologists performed lobewise correla

81 Radiologists and practice administrators should educate

82 oined twins are rare and pose a challenge to radiologists and surgeons.

83 kappa coefficients among the chest radiologists and the 5th-year radiology resident were 0.

84 Performances of radiologists and the artificial intelligence algorithm w

85 The interobserver agreement among radiologists and the majority report was between moderat

86 ccuracy, performs as well as musculoskeletal radiologists, and does not require manual image preproce

87 examined for opacities by two cardiothoracic radiologists, and scores were collated into a total conc

88 astroenterologists, surgeons, interventional radiologists, and specialists in critical care medicine,

89 C/UICC eighth edition changes, the impact on radiologists, and the rationale behind the changes will

90 andibular canals being coarsely annotated by radiologists, and using a dataset of 15 volumes with acc

91 Three radiologists annotated CT images obtained during the art

92 A fifth radiologist arbitrated results in case of discrepancies.

93 Diagnostic radiologists are experts in discriminating and classifyi

94 In this scenario, radiologists are key because they are involved in all as

95 Background Radiologists are proficient in differentiating between c

96 Even in large pediatric centers, radiologists are unlikely to encounter more than one suc

97 ltireader, multicase retrospective study, 14 radiologists assessed a dataset of 240 digital mammograp

98 Two radiologists assessed each CT in consensus and graded th

99 Two thoracic radiologists assessed embolic severity using the Mastora

100 Three radiologists assessed pre- and posttreatment MRI finding

101 e in PXS score in follow-up CXRs agreed with radiologist assessment (rho=0.74 (95%CI 0.63-0.81)).

102 s from noncontrast chest CT were superior to radiologists' assessment of extent and type of pulmonary

103 ow-up CXRs, PXS score change was compared to radiologist assessments of change (Spearman rho).

104 rence) were presented to six musculoskeletal radiologists at a tertiary cancer center in three image

105 ormance of board-eligible or board-certified radiologists at night compared with during the day.

106 AUC of 0.90 (88.6% accuracy), outperforming radiologist AUCs of 0.60 and 0.82 (P < .0001 and P = .16

107 AUC) of 0.84 (83.1% accuracy), outperforming radiologists' AUCs of 0.70 and 0.71 (P = .02 and P = .01

108 llustrate US and CT findings to increase the radiologists' awareness of this condition and to avoid d

109 egion that has traditionally been ignored by radiologists because most lesions can be diagnosed from

110 Two data sets were scored by two radiologists blinded to all clinical data; data set 1 co

111 Two radiologists blinded to clinical information assessed EP

112 2017, four fellowship-trained breast imaging radiologists blinded to final histologic findings interp

113 CT images were analyzed by two radiologists blinded to the RT-PCR results.

114 e dataset by two experienced musculoskeletal radiologists, blinded to clinical history.

115 ides surgical oncologists and interventional radiologists both macroscopic and microscopic views of c

116 was greater than the AUC-ROC for the average radiologist by an absolute margin of 11.5%.

117 the mADC value was measured by two different radiologists by using free-hand technique.

118 a group of technologists and as well as the radiologists.(C) RSNA, 2020.

119 hing that of two experienced musculoskeletal radiologists.(C) RSNA, 2020.

120 One radiologist calculated the tumour volume - manually meas

121 gence and machine learning algorithms to the radiologist can reduce image wait time and turnaround ti

122 th the return of other respiratory diseases, radiologists can play an important role in decision maki

123 The LR-5 category, determined through radiologist categorization of nodules using the CEUS LI-

124 Six radiologists categorized breast density on 451 mammogram

125 Two experienced radiologists categorized each chest radiograph as charac

126 Three thoracic radiologists circled pulmonary nodules, rating confidenc

127 identifying 17 of 25 (68%) patients, whereas radiologists classified all of these patients as COVID-1

128 Two radiologists classified each radiograph as adequate or i

129 Three technologists and three different radiologists classified the images in the test dataset,

130 om the Osteoarthritis Initiative staged by a radiologist committee using the Kellgren-Lawrence (KL) s

131 Radiologists consistently preferred DLR images (intracla

132 perintense T2 signal defined by a validation radiologist correlated with results of the test radiolog

133 The coordinating radiologist decided whether secondary recall was indicat

134 SWI can help radiologists detect findings not seen on conventional br

135 Radiologist diagnostic accuracy improved when receiving

136 For each image, a single radiologist dictated a standard phrase describing the le

137 ate, 3.0% [14 142 of 466 647]): 14 057 after radiologist double reading and 85 by the coordinating ra

138 Characteristics of cancers detected at radiologist double reading and those detected through qu

139 suspicious but that did not prompt recall at radiologist double reading.

140 nificantly from those of cancers detected at radiologist double reading.

141 ters in radiology reports, thereby improving radiologists' efficiency.

142 rpose To assess the real-life performance of radiologist emergency department chest CT interpretation

143 Three pediatric radiologists evaluated the success of the MRI study (whe

144 Two fellowship-trained cardiothoracic radiologists examined chest radiographs for opacities an

145 antial agreement with the original reporting radiologists for all three datasets (site 1 FFDM: linear

146 e developed algorithm performed similarly to radiologists for disease-extent contouring, which correl

147 uided procedures performed by interventional radiologists for impending pathologic fractures are beco

148 s performed by two experienced genitourinary radiologists for presence and maximum diameter of IFVs.

149 MR venography images were evaluated by three radiologists for presence of stenosis or occlusion.

150 ations were interpreted by 19 breast imaging radiologists from eight academic and 11 private practice

151 The radiologist had an agreement with the reference standard

152 For the 50-image subset, the best individual radiologist had an average F1 score of 0.60 and an accur

153 garding intraobserver variability, the first radiologist had nearly perfect concordance for compositi

154 l concordance for echogenic foci; the second radiologist had nearly perfect concordance for compositi

155 oncordance for echogenic foci, and the third radiologist had nearly perfect concordance for compositi

156 Both ML classifiers and radiologists had difficulty recognizing the chest radiog

157 Twenty-two of 32 (69%) radiologists had higher error rates for night cases (P =

158 in the latter half of assignments, with more radiologists having worse error rates at night compared

159 eline tumor volume (as defined by the "test" radiologist; hazard ratio = 11.3, P = 0.003).

160 o evaluate whether the algorithm could aid a radiologist in assessing splenic volume change.

161 scular anatomy that helps the interventional radiologist in pre-procedural planning.

162 O classification of STT that are relevant to radiologists in a routine clinical practice with MRI cor

163 udies independently interpreted off-hours by radiologists in an academic fellowship within 10 hours o

164 complicated or complicated appendicitis by 2 radiologists in blinded manner.

165 bjective vessel contrast was assessed by two radiologists in consensus.

166 ance similar to that of experienced thoracic radiologists in consensus.

167 These detected maps can help radiologists in differentiating benign and malignant les

168 We aim to provide guidance to radiologists in reporting CT findings potentially attrib

169 ication of bone tumours that are relevant to radiologists in routine clinical practice.

170 pected multi-organ imaging findings will aid radiologists in the assessment of these complex cases.

171 tool improved the diagnostic performance of radiologists in the detection of breast cancer without p

172 aluate whether the diagnostic performance of radiologists in the differentiation of cancer from nonca

173 s multidisciplinary update of the Society of Radiologists in Ultrasound consensus statement on liver

174 Two thoracic radiologists independently assessed all studies.

175 ces, baseline tumor size was recorded, and 2 radiologists independently estimated the percentage of t

176 Radiologists independently interpreted images from CT, w

177 Radiologists independently measured tumors in three dime

178 Two pediatric radiologists independently reviewed imaging for pattern,

179 Whole lung radiomics were superior to the radiologists' interpretation for predicting patient outc

180 n, and gastrointestinal imaging may confound radiologists' interpretation of cancer diagnosis, stagin

181 atient with an AUC of 0.84 (P < .005), while radiologists' interpretations of disease extent and opac

182 ed screws as performed by the interventional radiologist is a safe nonsurgical treatment that provide

183 Automatic analysis was faster than the two radiologists' manual measurements (3 vs 36 vs 35 seconds

184 be discussed to help ensure that diagnostic radiologists may be of greatest use to the ordering phys

185 A blinded radiologist measured T2-weighted signal intensity (SI) r

186 laboration between engineers, interventional radiologists, medical oncologists, and immuno-oncologist

187 hopaedic radiology practice, musculoskeletal radiologists must be familiar with the imaging appearanc

188 aced with the finding of a small renal mass, radiologists must determine whether it is benign or mali

189 or guiding further management decisions, and radiologists must understand expected treatment-specific

190 36% for TDx; P < .001 for both) and general radiologists (n = 2; 53% for T3DDx, 31% for TDx; P < .00

191 ent pancreas outlines by two board-certified radiologists (n = 30) yielded an ICC of 0.945 (95% CI 0.

192 including pulmonologists (n = 17), thoracic radiologists (n = 5), and thoracic surgeons (n = 2), was

193 All radiologists need to be able to recognize the direct and

194 Radiologists need to be familiar with the imaging findin

195 Radiologists need to be familiar with these developments

196 are accompanied by new adverse effects that radiologists need to know.

197 s compared with radiology residents, general radiologists, neuroradiology fellows, and academic neuro

198 The exposure to the head of radiologist, nurse and radiographer was 2.1muSv, 1.4muSv

199 The radiologist, nurse and radiographer were exposed to a wh

200 Additionally, The radiologist, nurse and radiographer whole body and lens

201 e the radiation exposure to locations that a Radiologist, Nurse and Radiographer would be standing du

202 y comparing diagnostic accuracy with that of radiologists of varying levels of specialization by usin

203 There were 110 interpreting radiologists, of whom 24 were defined as high-volume rea

204 terpretations from five experienced thoracic radiologists on 300 random test images using the McNemar

205 This review discusses radiologists' opinions on the topic and suggests trends

206 versus rare diagnoses (78% vs 47% across all radiologists; P < .001).

207 ractitioners, gastroenterologists, surgeons, radiologists, pain specialists, and nutritional therapis

208 wo thoracic radiologists and one in-training radiologist (Pearson r).

209 attention on the impact of overnight work on radiologist performance.

210 ce imaging (mpMRI) has been shown to improve radiologists' performance in the clinical diagnosis of b

211 f an artificial intelligence system improves radiologists' performance in the task of differentiating

212 ty and specificity, examined per quartile of radiologists' performance.

213 Three pediatric radiologists performed an observer study to assess anato

214 Two musculoskeletal radiologists performed measurements on fully and semiaut

215 Radiologists play an important role in the detection and

216 el-wise manner by two readers (neurosurgeon, radiologist) provided the reference standard.

217 ric and adult neuro-oncologists, clinicians, radiologists, radiation oncologists, and neurosurgeons,

218 ric and adult neuro-oncologists, clinicians, radiologists, radiation oncologists, and neurosurgeons,

219 Two blinded radiologists (radiologist 1 and radiologist 2) assessed

220 learning model (GPDL-BAAM) and two pediatric radiologists (radiologists 1 and 2) using the GP method.

221 XR was 82%, compared with that of individual radiologists (range, 76%-81%) and the consensus of all f

222 hereas the median DSCs between contours from radiologists ranged from 0.68 to 0.71.

223 nsensus technologists' rating, and consensus radiologists' rating to the ground truth were 0.76 (95%

224 Radiologist ratings were 7 +/- 1 (DLR), 6.2 +/- 1 (MBIR)

225 , independently partially annotated by three radiologist readers.

226 ent of osteoarthritis still relies on expert radiologists' readings.

227 The goal of this expert consensus is to help radiologists recognize findings of COVID-19 pneumonia an

228 e technologists and a coordinating screening radiologist regularly discussed mammograms that the tech

229 Fellowship-trained abdominal radiologists reinterpreted transvaginal US findings by u

230 despread use of MRI for these purposes, many radiologists remain unfamiliar with the complex anatomy

231 Radiologists reported lung and non-lung-related abnormal

232 The radiologist reports of all consecutive patients who had

233 Qualitative reviews by radiologists revealed the potential benefits and pitfall

234 Three breast radiologists reviewed images in random order, including

235 Two radiologists reviewed independently and blinded the imag

236 Four radiologists reviewed test set images for performance co

237 Three pediatric radiologists reviewed the image volumes without knowing

238 Radiologist reviews revealed the overall quality of PET(

239 iologist correlated with results of the test radiologist (rho = 0.75).

240 o significant performance difference between radiologist's and artificial intelligence algorithm: art

241 teristic curve of 0.737 (0.659-0.815) versus radiologist's area under the receiver-operating characte

242 teristic curve of 0.740 (0.662-0.817) versus radiologist's area under the receiver-operating characte

243 We believe that the radiologist's knowledge of the prevalence and pattern of

244 Radiologist's maximum sensitivity up to 0.87 (95% CI, 0.

245 Two thoracic radiologists scored the CT extent of mosaic attenuation,

246 he collective experience of private-practice radiologists shared with members of the Radiological Soc

247 , if fatty infiltration is seen in isolation radiologist should look for foreign body.

248 Radiologists should be familiar with the imaging manifes

249 To assess image quality, two independent radiologists subjectively evaluated the visualization of

250 members of the panel - gastroenterologists, radiologists, surgeons and oncologists -were selected on

251 In an independent study of six radiologists, the AI system outperformed all of the huma

252 This ability would make ensure for the radiologist to do biopsy or not, especially in the cases

253 rd technique was completed by three thoracic radiologists to assess image quality.

254 Additionally, opportunities for radiologists to contribute to research that may influenc

255 ttributable to COVID-19 pneumonia, requiring radiologists to decide whether or not to mention COVID-1

256 segment the spleen on CT scans and may help radiologists to detect abnormal splenic volumes and sple

257 d retrospectively by board-certified nuclear radiologists to determine true or false positivity based

258 or with artificial intelligence (AI), allows radiologists to improve diagnoses that may improve patie

259 nd its ultrasonographic features will enable radiologists to suggest its diagnosis and to include it

260 We aim to enhance radiologists' understanding of this disease to help guid

261 Given that many radiologists undertake their doctoral theses once their

262 The other radiologist used the syngo.CT-Liver-Analysis software to

263 age test set, and compared to two individual radiologists using a 50-image test subset.

264 reement on breast density within and between radiologists using the criteria established in the fifth

265 Two blinded radiologists visually and qualitatively scored contrast

266 Three independent blinded radiologists visually scored tumor conspicuity (subjecti

267 y in reporting between a senior and a junior radiologist was evaluated.

268 The kappa coefficient among the chest radiologists was 0.663 (95% confidence interval [CI]: 0.

269 The compatibility of the two radiologists was evaluated with kappa statistical analys

270 The correlation between radiologists was found to be different for different loc

271 , 0.36 [95% CI: 0.29, 0.43]), while that for radiologists was moderate (Fleiss kappa, 0.59 [95% CI: 0

272 Agreement between the radiologists was substantial for T2-weighted SI (Cohen k

273 rmance differences between the algorithm and radiologists, we regard artificial intelligence as a pro

274 Manual segmentations by an experienced radiologist were used as reference.

275 est images, respectively, the ICCs of AI and radiologists were 0.84 (95% CI: 0.78, 0.92) and 0.89 (95

276 d 0.89 (95% CI: 0.77, 0.94); the ICCs of the radiologists were 0.93 (95% CI: 0.90, 0.95) and 0.84 (95

277 Radiologists were also asked to identify suspected lesio

278 Radiologists were blinded to the supine chest radiograph

279 Performance metrics of the model and of the radiologists were compared by using the McNemar test, an

280 ttee, EDSS raters, laboratory personnel, and radiologists were masked to the treatment assignment, bu

281 Radiologists were more accurate at diagnosing common ver

282 ification by TA and visual classification by radiologists were performed to discriminate among the th

283 Contrast thresholds of radiologists were superior to the control groups in all

284 This occurrence should be considered by the radiologist when a new lesion is detected, especially if

285 ion of the MRI itself, the experience of the radiologist, whether additional biomarkers are considere

286 ncreases the degree of confidence in a novel radiologist, while in the expert its use is less relevan

287 ogical studies were reviewed by an abdominal radiologist who was blinded to the pathological results.

288 ere quantified and image quality scored by a radiologist who was masked to the method of data process

289 m accuracy was referenced to board-certified radiologists who evaluated supine chest radiographs acco

290 Moreover, cycle-GAN fooled two experienced radiologists who identified fake chest radiographs as be

291 overpredict age for younger children versus radiologists who showed a consistent mean bias.

292 evaluated the cycle-GAN's ability to mislead radiologists who were asked to perform the same recognit

293 being double read by two certified screening radiologists who were not blinded to the technologists'

294 teen patients were also analysed by a second radiologist with a similar experience level as that of t

295 Recently, the low familiarity of the radiologist with this condition has been emphasized.

296 Cross-sectional study; three radiologists with different levels of experience used th

297 Two radiologists with more than seven years of experience re

298 tutions, exceeding the diagnostic ability of radiologists with specialized head and neck experience.

299 ammograms were interpreted by breast imaging radiologists with the assistance of computer-aided detec

300 t is to describe the specific experiences of radiologists working in various types of private radiolo