ライフサイエンスコーパス: chest X-ray

1 ct the risk of lung disease mortality from a chest x-ray.

2 -dose chest CT was almost equal to that of a chest X-ray.

3 he diagnosis of thoracic pathology by simple chest X-ray.

4 ever, hypoxia, and ground-glass opacities on chest X-ray.

5 te aortic calcification was present on prior chest X-ray.

6 ecificity of 98% in detecting pneumonia from chest X-rays.

7 ick and accurate diagnosis of pneumonia from chest X-rays.

8 mmon lung diseases are first diagnosed using chest X-rays.

9 g inputs of vital signs, laboratory data and chest X-rays.

10 tection and localization of abnormalities on chest X-rays.

11 itecture capable of detecting pneumonia from chest X-rays.

12 inspired fraction of oxygen (FiO2) ratio and chest X-rays.

13 monic progression of COVID-19 on consecutive chest X-rays.

14 uantiferon Gold (Q-G) positive with negative chest X-rays.

15 IgE, IgA, and IgG; and abnormal results from chest x-rays.

16 n of recurrent disease was CEA testing (30), chest x-ray (12), colonoscopy (14), and other (40).

17 eNet using the National Institutes of Health Chest X-ray 14 dataset (112 120 images) and MURA dataset

18 4, 0.95) versus 0.83 (95%, CI 0.83, 0.84) on Chest X-Ray 14, 0.84 (95% CI: 0.77, 0.91) versus 0.83 (9

19 cation using four public datasets: CheXpert, Chest X-Ray 14, MIMIC CXR, and VinBigData.

20 ssification performance was evaluated on the Chest X-Ray 14, VinBigData, and Society for Imaging Info

21 ed Chest CT-All DI consisted of (1) abnormal chest X-ray, (2) rapid deceleration mechanism, (3) distr

22 lts >=15 years) were screened with miniature chest X-ray; 2,369 (0.4%) were diagnosed with tuberculos

23 Eighty-three (75%) had cavities on chest X-ray, 55 (50%) had a smear grading of 3+, and the

24 ted with reason for imaging (P<0.001), year (chest x-ray 67% in 2000-2004 vs. 49% in 2005-2009; P<0.0

25 ), computed tomography scan (23.6% v 26.4%), chest x-ray (7.3% v 12.1%), and colonoscopy (12.7% v 8.8

26 Chest X-ray, abdominal ultrasound, chest and abdominal C

27 The AI system accurately detected chest X-ray abnormalities (AUC: 0.976, 95% bootstrap CI:

28 everity of sarcoidosis was assessed based on chest X-ray abnormalities.

29 As a result, weakly supervised chest X-ray abnormality localization is gaining increasi

30 study, we propose a novel WSOL framework for chest X-ray abnormality localization that uses VMamba as

31 ng interest in building automated systems of chest X-ray abnormality localization.

32 ein, interleukin-6 level, and procalcitonin; chest X-ray abnormality, and intensive care unit/ventila

33 events included rearrest, pulmonary edema on chest x-ray, acute renal dysfunction, bleeding requiring

34 called EXAM (electronic medical record (EMR) chest X-ray AI model), that predicts the future oxygen r

35 tern of these infections is nonspecific, and chest X-rays alone are insufficient for the diagnosis.

36 varying difficulty: (1) histopathology, (2) chest X-ray and (3) dermatology images.

37 Chest X-ray and abdominal computed tomography revealed g

38 examination-and might the radiologist with a chest X-ray and abdominal ultrasound do better?

39 (including cysticercosis and echinococcus), chest x-ray and abdominal ultrasound found no evidence o

40 with new or worsening alveolar shadowing on chest X-ray and clinical/hematological parameters suppor

41 The DTS images were far superior to chest x-ray and comparable with CT in evaluating the pla

42 s confirmed by RT-PCR test and who underwent chest X-ray and computed tomography (CT) studies to asse

43 The most common chest X-ray and computed tomography abnormality was mult

44 Chest X-ray and CT revealed diffuse granular shadow in t

45 The patient underwent chest X-ray and CT scan, which showed right sided pleura

46 Both chest X-ray and CT severity scores (CT-SS) were recorded

47 ortality reduction among those randomized to chest x-ray and cytology.

48 om history and tuberculin skin testing, with chest x-ray and GeneXpert Ultra for confirmatory testing

49 The threshold values of chest X-ray and HRCT quantitative parameters were calcul

50 e did not use sensitive screening tools like chest X-ray and likely missed people with TB.

51 tient with asthma to be afebrile with normal chest x-ray and white blood cell count.

52 We reviewed 15 chest X-rays and 10 chest computed tomography (CT) studi

53 Plain chest X-rays and computed tomography (CT) scan are the m

54 and features within medical images, such as chest X-rays and CT scans.

55 dy analyzed the relationship between initial chest X-rays and initial laboratory tests in symptomatic

56 ned on ImageNet is first fine-tuned on human Chest X-rays and then fine-tuned again on 500 annotated

57 ted using both TDA A (an algorithm including chest X-ray) and TDA B (without chest X-ray), excluding

58 ms or computer-aided-detection score >=40 on chest x-ray) and whose sputum was tested with Xpert Ultr

59 ng Data for Localization of Abnormalities in Chest X-rays) and EGD-CXR (Eye Gaze Data for Chest X-ray

60 nely evaluated by physical examination, ECG, chest X-ray, and 24-hour Holter.

61 participants underwent clinical examination, chest x-ray, and blood sampling, and were requested to p

62 , carcinoembryonic antigen (CEA) assessment, chest x-ray, and colonoscopy in detecting recurrent dise

63 diagnosed with outpatient CAP, evaluated via chest x-ray, and dispensed a same-day CAP-related oral a

64 amin intake, normal liver function, negative chest x-ray, and no other evidence of recurrence.

65 onary failure, with bilateral infiltrates on chest x-ray, and PaO2/fraction of inspired oxygen (FiO2)

66 teral-flow lipoarabinomannan assay (LF-LAM), chest x-ray, and sputum culture.

67 had more bone scans, tumor antigen testing, chest x-rays, and chest/abdominal imaging than other wom

68 Chest CT is more sensitive than plain chest X-rays, and CT studies make it possible to identif

69 We measured bone scans, tumor antigen tests, chest x-rays, and other chest/abdominal imaging during 3

70 Blood pressure measurements, chest x-rays, and tests of blood and sputum were taken t

71 et was 4,200, among which, 3,500 were normal chest X-rays, and the remaining 700 X-ray images were of

72 Social and health questionnaires, chest X-rays, and Xpert MTB/RIF were performed.

73 ck-years), history of myocardial infarction, chest x-ray appearance, bloodstream infection, and the o

74 Chest X-rays are a frequently used imaging modality for

75 As portable chest X-rays are an efficient means of triaging emergent

76 Chest x-rays are extremely limited in their ability to d

77 Although chest X-rays are the initial imaging technique of choice

78 Chest X-rays are the most commonly performed medical ima

79 Because chest X-rays are widely available and deliver relatively

80 clinical variables such as age and abnormal chest x-ray as well as cytokines such as macrophage colo

81 rsening by classifications of involvement in chest X-rays as moderate or severe.

82 er (ViT) architecture on a public dataset of chest X-rays available on Kaggle.

83 differences in the percentage of pathologic chest X-rays between patients hospitalized in the ICU (7

84 ry function tests, arterial blood gases, and chest X-rays, but the correlation with lung pathology is

85 s diagnosed by examining the posteroanterior chest X-rays by a radiologist and graded into four group

86 ts, chest pain, and fever for >=2 weeks), or chest X-ray CAD4TBv5 score >=50, or no available X-ray r

87 analysed the effect of the 1957 Glasgow mass chest X-ray campaign to inform contemporary approaches t

88 nts with low clinical suspicion and negative chest X-rays can be discharged with a low probability of

89 Chest x-rays, CBCs, and liver function tests are not rec

90 Participants received chest-X-ray, Cepheid Xpert TB Host Response (Xpert HR) t

91 Use of chest X-ray, chest computed tomography scan, abdominal a

92 adiology reports from the Indiana University chest x-ray collection available from the National Libra

93 nal Library of Medicine's Indiana University Chest X-ray Collection.

94 ical examination, liver function tests, CEA, chest X-ray, computed tomography scan of the abdomen, an

95 function studies, carcinoembryonic antigen, chest x-ray, computed tomography scans, and endoscopies

96 years) admitted to 4 Spanish hospitals with chest X-ray-confirmed CAP between November 2011 and Nove

97 iography, Lateral Chest Radiography, Lateral Chest X-ray Coronary Calcium, Coronary Calcium Screening

98 abnormality detection tasks, specifically in Chest X-Ray (CXR) analysis, followed by breast mammogram

99 underwent standard TB assessments, including chest X-ray (CXR) and sputum Xpert Ultra testing, follow

100 ominated by CT and a detailed description of chest x-ray (CXR) appearances in relation to the disease

101 es were consistently lower than rates in the chest X-ray (CXR) arm.

102 ts with confirmed SARS-CoV-2 infection, with chest X-ray (CXR) findings probable or indeterminate for

103 e World Health Organization (WHO) recommends chest X-ray (CXR) for TB screening and triage, given its

104 ed risk-tool based on minimal parameters and chest X-ray (CXR) image data that predicts the survival

105 Chest X-ray (CXR) images are one of the most readily ava

106 We developed a test library of chest X-ray (CXR) images which was blindly re-read by tw

107 approach for being applicable in the case of chest X-Ray (CXR) images.

108 ognitive processes and predicts scanpaths in chest X-ray (CXR) images.

109 and capabilities for testing lagged behind, chest X-ray (CXR) imaging became more relevant in the ea

110 patients, physical examination (PE) in 14%, chest x-ray (CXR) in 23%, and abdominal x-ray (KUB) in 7

111 ng (CTLS) versus either no screening (NS) or chest x-ray (CXR) in subjects with cigarette smoking his

112 ormula: see text] 0.01when the corresponding chest x-ray (CXR) is consistent with interstitial edema

113 Chest X-ray (CXR) is generally considered not to be sens

114 mes were weight gain and an improvement in a chest X-ray (CXR) lesion assessed at 6 mo of treatment.

115 of mechanical ventilation (MV) and portable chest X-ray (CXR) measurements of lung length (LL) and s

116 Chest x-ray (CXR) measurements to estimate actual total

117 nd neck squamous cell carcinoma (HNSCC) than chest x-ray (CXR) plus head and neck MRI or chest CT (CC

118 ed detection software (CAD) could facilitate chest X-ray (CXR) use in tuberculosis diagnosis.

119 Chest transthoracic ultrasound (US), chest X-ray (CXR), and computed tomography (CT) were per

120 Chest X-ray (CXR), computed tomography (CT), and positro

121 Spatial resolution in existing chest x-ray (CXR)-based scoring systems for coronavirus

122 final clinical diagnosis, and secondarily to chest X-ray (CXR).

123 Original readings of chest X-rays (CXR) and computerized tomography (CT) were

124 udy was to analyse the texture parameters of chest X-rays (CXR) of patients suspected of having COVID

125 Chest-X ray (CXR) radiography can be used as a first-lin

126 Chest radiography (chest x-ray [CXR] and chest computed tomography [CT]) is

127 g opportunities for insights from a standard Chest X-Ray [CXR].

128 Chest x-rays (CXRs) are often used to assess SARS-CoV-2

129 Chest X-rays (CXRs) are primarily used to detect lung le

130 Chest X-rays (CXRs) are routinely conducted on a broad p

131 Chest X-rays (CXRs) are the first-line investigation in

132 Chest X-rays (CXRs) are widely used for diagnosing respi

133 he role of portable, anteroposterior, supine chest X-rays (CXRs) in distinguishing hydrostatic pulmon

134 classify the severity of COVID-19 using 1208 chest X-rays (CXRs) of 396 COVID-19 patients obtained th

135 Chest X-rays (CXRs) were conducted as standard care for

136 mized to intervention, receiving four annual chest x-rays (CXRs), or to control, receiving usual care

137 The CAD system processes chest X-ray data and provides accurate, objective imagin

138 commonly used chest X-ray datasets, the NIH chest X-ray dataset and the RSNA dataset, and demonstrat

139 mans, and conduct experiments on a pneumonia chest X-ray dataset with over 5000 images.

140 f a pneumonia detection algorithm in a large chest X-ray dataset.

141 licly available dataset, as well as COVID-19 Chest X-rays dataset.

142 pathology classification across three large chest X-ray datasets, as well as one multi-source datase

143 sed method is evaluated on two commonly used chest X-ray datasets, the NIH chest X-ray dataset and th

144 Using two popular chest x-ray datasets, we first demonstrate that technica

145 mology-and incorporates data from six global chest X-ray datasets.

146 Digital chest X-ray (dCXR) computer-aided detection (CAD) techno

147 screening, including computer-aided digital chest X-ray (DCXR-CAD).

148 Rates of tumor antigen testing and chest x-rays decreased faster and chest/abdominal imagin

149 A chest x-ray demonstrated a right-upper-lobe opacity.

150 AM10000 (dermatoscopic images) and CheXpert (chest x-rays), demonstrating its effectiveness in divers

151 the-art vision-language foundation models in chest x-ray diagnosis across five globally sourced datas

152 AI assistance on 140 radiologists across 15 chest X-ray diagnostic tasks and identified predictors o

153 The analysis of chest X-ray doses was made on the basis of reports from

154 re doses delivered in low dose chest CT with chest X-ray doses.

155 rategies were compared with existing policy (chest x-ray during visa application).

156 pairs to train a specialized, domain-adapted chest X-ray encoder.

157 is accurate and reduces physician errors in chest X-ray evaluation, which highlights the potential o

158 lowed for 4 years with blood chemistries and chest x-ray every 3 months for year 1, every 4 months fo

159 ments in favor of lung cancer screening with chest x-ray examination and sputum cytology, a practice

160 predicted for LDCT may exceed those used in chest X-ray examinations by a factor of 4 to 12, dependi

161 uspected SARS-CoV-2 infections who underwent chest X-ray examinations in the emergency department of

162 ologist physicians detected abnormalities on chest X-ray exams as accurately as radiologists when aid

163 hm including chest X-ray) and TDA B (without chest X-ray), excluding the triage step.

164 Chest X-ray film and pulmonary function tests with diffu

165 reening tests began in the 1950s with annual chest x-ray films and sputum cytology but they resulted

166 e emphasizes that the abnormalities noted on chest x-ray films of the chest can be diagnostic of gian

167 on, and work of breathing) are negative, the chest x-ray findings are unlikely to be positive.

168 Conclusion Chest x-ray findings in COVID-19 patients frequently sho

169 e a scale of radiologic severity to classify chest X-ray findings in diagnosing patients with COVID-1

170 analyze the relationship between the initial chest X-ray findings in patients with severe acute respi

171 l pro-brain natriuretic peptide, distinctive chest x-ray findings, and relationship with existing res

172 ed age, brain death, neurological diagnoses, chest x-ray findings, PaO2/FiO2, creatinine, alanine tra

173 tic lead malfunction can present with normal chest X-ray findings.

174 A chest x-ray followed by a chest computed tomography scan

175 included baseline questionnaire, spirometry, chest X-ray, food frequency questionnaire, and serum bet

176 onsent, each participant underwent a digital chest X-ray for CAD4TBv7 and a CRP test.

177 mputed tomography as opposed to conventional chest x-ray for pulmonary surveillance is costly and pro

178 raphy and lung ultrasound are noninferior to chest x-ray for screening of pneumothorax and accurate c

179 imaging modalities have decreased the use of chest X-rays for differentiating between true abnormalit

180 ge, 4 y, range 1 month - 16 years) underwent chest X-rays for suspected respiratory infections.

181 Evaluated on lung segmentation in chest X-rays for tuberculosis detection, HybridMS achiev

182 study, we present MaCo, a masked contrastive chest X-ray foundation model that tackles these challeng

183 itial fibrosis as identified on the baseline chest X-ray, from 0.9% to 2.4%, 10.8%, and 35.4% for Int

184 cted initially by CT scan without antecedent chest x-ray has increased considerably.

185 19) has been a diagnostic challenge in which chest X-rays have had a key role.

186 atients with RT-PCR positive for SARS-CoV-2, chest X-rays have no prognostic usefulness.

187 clinically used imaging strategies based on chest x-ray + head and neck MRI (CXR/MRI) and chest CT +

188 n; urine toxicology test; electrocardiogram; chest x-ray; head-to-pelvis computed tomography; and bed

189 causes was evaluated with clinical data and chest X-ray image data.

190 ism to adjust the correlation between masked chest X-ray image patches and their corresponding report

191 ate diverse and visually plausible synthetic chest X-ray images (as confirmed by board-certified radi

192 by leveraging publicly available datasets of chest X-ray images and the corresponding radiology repor

193 This study aims to enhance TB detection in chest X-ray images by developing deep learning models.

194 Using 2500 chest X-ray images consisting of 1250 COVID-19 and 1250

195 However, interpretation of chest X-ray images depends on the radiologist's competen

196 Net segmentation model was trained using 704 chest X-ray images sourced from the Montgomery County an

197 show that a self-supervised model trained on chest X-ray images that lack explicit annotations perfor

198 be used to detect COVID-19 infection in the chest X-ray images, and Epistocracy algorithm can be eff

199 learning pipeline for the standardization of chest X-ray images, for the visualization of lesions and

200 e dataset comprising a diverse collection of chest X-ray images, that included both positive and nega

201 lobal context and spatial relationships from chest X-ray images, the proposed framework deploys the V

202 eep models used for identifying anomalies in chest X-ray images.

203 iology by generating free-text findings from chest X-ray images.

204 rts to classify COVID-19 lung infection from chest X-ray images.

205 und, thereby improving their separability in chest X-ray images.

206 he accuracy and precision of TB detection in chest X-ray images.

207 Chest-X-ray images were processed using CAD4TB v7, a com

208 ng capacity of carbon monoxide (DL(CO)), and chest X-ray in 16 cases (5.2%); clinical history, DL(CO)

209 f effective radiation dose comparable with a chest x-ray in 2 views.

210 ormal in 38 patients, and the sensitivity of chest X-ray in diagnosing SARS-Cov-2 was 54%.

211 orrhea, cough, and/or dyspnea) that required chest X-rays in our hospital between March 1 and March 3

212 Chest X-rays in patients with COVID-19 obtained in the e

213 Thus, widely available chest X-rays, in conjunction with clinical information,

214 ral catheter (IPC) when lung re-expansion on chest X-ray is incomplete.

215 Chest X-ray is usually the first imaging modality to rai

216 Chest X-ray is widely used to diagnose lung diseases.

217 Interpreting chest X-rays is a complex task, and artificial intellige

218 Chest X-rays lacked definite signs of pneumonia, a defin

219 AI's capacity to infer demographic data from chest X-rays, leading to a key concern: do models using

220 Chest X-ray lesion characteristics of MDR-TB show signif

221 Furthermore, chest x-rays, lung function, and PaO2/FIO2 ratios did no

222 Early in infection, an abnormal chest X ray, M. tuberculosis growth by gastric aspirate,

223 seful where other recommended tools, such as chest x-ray, might not be readily available.

224 Initial chest x-ray most commonly showed bilateral infiltrates,

225 r lower respiratory infections necessitating chest X-rays (NA-LRIs), nasopharyngeal pneumococcal carr

226 Follow-up on abnormal chest x-ray (odds ratio [OR], 2.07; 95% CI, 1.04 to 4.13

227 uating Hospital Admission (RSEHA) applied to chest X-rays of patients with COVID-19 when they present

228 exposure history, a physical examination, a chest x-ray or computed tomography to rule out thymoma,

229 cts lung cancer 2 years earlier than routine chest x-ray or cytomorphology.

230 subjects underwent annual review since 1990, chest X-ray or low-dose computed tomography scan, and ou

231 f correct management as at least a referral, chest X-ray or sputum test, 41% (111 of 274) SPs were co

232 (SPN) is a common radiologic abnormality on chest x-rays or computed tomography (CT) scans of the lu

233 re determined by a semiquantitative score of chest x-rays or computed tomography scans performed with

234 CI, 1.3-3.2), pleural effusion on presenting chest x-ray (OR, 1.6; 95% CI, 1.1-2.4), and inpatient ca

235 ion, evidence for pulmonary edema on initial chest x-ray, or rearrest.

236 izing texture features derived from emergent chest X-rays, particularly among older patients or those

237 re, we examine algorithmic underdiagnosis in chest X-ray pathology classification across three large

238 lusive of a secondary screen approximated by chest x-ray performance).

239 skin test conversion were required to have a chest x-ray performed and see a physician and were encou

240 the traditional imaging strategies based on chest x-ray plus head and neck MRI (CXR/MRI) or chest CT

241 ficiency of our system in diagnosing TB from chest X-rays, potentially surpassing clinician-level pre

242 A single, rapid round of mass screening with chest X-ray (probably the largest ever conducted) likely

243 load, 24.0%), and pulmonary function testing/chest x-ray (pulmonary dysfunction, 84.1%).

244 udy uses the classification of COVID-19 from chest x-ray radiographs as an example to demonstrate tha

245 or 1/3 the maximum intrathoracic diameter on chest x-ray) received two cycles of doxorubicin, bleomyc

246 assessed by means of coronary venograms and chest x-rays recorded at the time of device implantation

247 l risk markers present (ADD score 0), 72 had chest x-rays recorded, of which 35 (48.6%) demonstrated

248 iologists, serving as a secondary reader for chest X-rays, reducing reporting turnaround times, aidin

249 s among participants with differing baseline chest X-ray results were assessed.

250 (71%), mild disease (76%), and mainly normal chest x-ray results.

251 Chest x-ray revealed cardiomegaly and pulmonary vascular

252 Risk factors included abnormal chest X-ray (risk ratio [RR], 1.21; 95% credible interva

253 was applied to segment lung regions in 1400 chest X-ray scans, encompassing both TB cases and normal

254 emic era calls for appropriate literature on chest X-ray score cut-offs, enabling swift categorizatio

255 Age, 17 blood analytes, and Brescia chest X-ray score were the variables processed using a r

256 , ferritin std, and monocyte %), and Brescia chest X-ray score.

257 rs of age the screened patients showed worse chest X-ray scores associated with earlier acquisition o

258 Moderate/severe extension in the three chest X-ray scoring systems evaluating the extent of inv

259 Including chest X-ray screening alongside TB symptom screening cou

260 fessional societies call for routine staging chest x-rays (SCXR) for all patients with invasive cance

261 A preprocedure chest x-ray showed a right lower lobe infiltrate.

262 A chest x-ray showed bilateral hilar enlargement, thickeni

263 Chest X-ray showed diffuse ground-glass shadows in both

264 Postoperative portable chest x-rays showed the ECG method to position the cathe

265 ronchial stents in whom we performed DTS and chest x-ray simultaneously.

266 ,377 male North American insulators for whom chest X-ray, spirometric, occupational, and smoking data

267 tested and volunteers underwent spirometry, chest x-ray study, and a bronchoalveolar lavage.

268 unity to examine factors captured on implant chest x-ray that correlate with risk for lead conductor

269 ment to investigate the result of a previous chest X-ray that showed bilateral mediastinal enlargemen

270 ng their most characteristic distribution on chest X-rays, the main diagnostic modality used for thor

271 On an external validation dataset of chest X-rays, the self-supervised model outperformed a f

272 In an independent set of 440 chest X-rays, the system performed comparably to senior

273 een developed, such as the interpretation of chest X-ray to rule out pathology.

274 Chest X-rays) and EGD-CXR (Eye Gaze Data for Chest X-rays) to develop a collaborative AI solution, na

275 ion, complete blood count with differential, chest x-ray, urinalysis and culture, electrolyte panel,

276 Additionally, an expert radiologist read the chest X-rays via teleradiology.

277 The detection rate for chest x-ray was 0.9%, the total cost was $120,934, and t

278 atio between medial doses in low dose CT and chest X-ray was 11.56.

279 Abnormal chest x-ray was the clue most frequently associated with

280 s evaluated "deep learning" systems in which chest X-ray was used for the diagnosis of infectious dis

281 tuberculosis among persons with an abnormal chest X-ray was very high.

282 SARS-CoV-2 was 70.4%, and the sensitivity of chest X-rays was 62.8%.

283 Chest x-rays was normal.

284 e of AI systems for the automatic reading of chest X-ray were selected.

285 The most common findings on chest X-rays were consolidation (86%), nodules (26%), an

286 acification on repeat CT imaging, and normal chest X-rays were found in 93% of patients with mild dis

287 In the group of patients without RT-PCR, chest X-rays were negative in 97.5%, corroborating the l

288 Chest X-rays were normal in 38 patients, and the sensiti

289 encephalitis and 9 out of 11 patients whose chest X-rays were obtained had bilateral infiltrates.

290 t improvements in detecting abnormalities on chest X-rays when aided by the AI system compared to whe

291 the AI system and were faster at evaluating chest X-rays when aided compared to unaided.

292 The lungs are the main organ involved, and chest X-rays, whether obtained in conventional X-ray sui

293 ed diuretic use and pulmonary edema on first chest x-ray, which resolved within 24 hours after admiss

294 We evaluated digital chest X-ray with computer-aided detection (CAD) software

295 nd Determine-LAM, Alere/Abbot, USA), digital chest X-ray with computer-aided diagnosis (dCXR-CAD, CAD

296 dose reduction which would permit replacing chest X-ray with low dose CT in certain research screeni

297 ndamentally linear atelectasis) in the first chest X-ray with pathologic findings.

298 -19 Radiography Database containing labelled chest X-rays with differing pathologies via the Frechet

299 articipants were screened on TB symptoms and chest X-ray, with diagnostic testing using Xpert-Ultra f

300 inely capture anterior posterior and lateral chest x-rays within 2 weeks of implant.