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Receiver-operating characteristic (ROC) plots: a fundamental evaluation tool in clinical medicine
Abstract
The clinical performance of a laboratory test can be described in terms of diagnostic accuracy, or the ability to correctly classify subjects into clinically relevant subgroups. Diagnostic accuracy refers to the quality of the information provided by the classification device and should be distinguished from the usefulness, or actual practical value, of the information. Receiver-operating characteristic (ROC) plots provide a pure index of accuracy by demonstrating the limits of a test's ability to discriminate between alternative states of health over the complete spectrum of operating conditions. Furthermore, ROC plots occupy a central or unifying position in the process of assessing and using diagnostic tools. Once the plot is generated, a user can readily go on to many other activities such as performing quantitative ROC analysis and comparisons of tests, using likelihood ratio to revise the probability of disease in individual subjects, selecting decision thresholds, using logistic-regression analysis, using discriminant-function analysis, or incorporating the tool into a clinical strategy by using decision analysis.
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Cites
DeLong, E. R., DeLong, D. M., & Clarke-Pearson, D. L. (1988) · Biometrics · doi:10.2307/2531595 · Cited by 22,649
Assessment of diagnostic tests when disease verification is subject to selection bias
Begg, C. B., & Greenes, R. A. (1983) · Biometrics · doi:10.2307/2530820 · Cited by 708
Evaluating diagnostic tests with imperfect standards
Valenstein, P. N. (1990) · American Journal of Clinical Pathology · doi:10.1093/ajcp/93.2.252 · Cited by 220 · cited 1×
“One strategy is to define the diagnostic problem in terms of measurable clinical outcomes (64).”
Background
Cited by
Maximum entropy modeling of species geographic distributions
Phillips, S. J., Anderson, R. P., & Schapire, R. E. (2006) · Ecological Modelling · doi:10.1016/j.ecolmodel.2005.03.026 · Cited by 15,396
The validity of the Hospital Anxiety and Depression Scale
Bjelland, I., Dahl, A. A., Haug, T. T., & Neckelmann, D. (2002) · Journal of Psychosomatic Research · doi:10.1016/s0022-3999(01)00296-3 · Cited by 9,779
A review of methods for the assessment of prediction errors in conservation presence/absence models
FIELDING, A. H., & BELL, J. F. (1997) · Environmental Conservation · doi:10.1017/s0376892997000088 · Cited by 6,956
ALLOUCHE, O., TSOAR, A., & KADMON, R. (2006) · Journal of Applied Ecology · doi:10.1111/j.1365-2664.2006.01214.x · Cited by 5,172
Anderson, N. L., & Anderson, N. G. (2002) · Molecular & Cellular Proteomics · doi:10.1074/mcp.r200007-mcp200 · Cited by 4,414
AUC: A misleading measure of the performance of predictive distribution models
Lobo, J. M., Jiménez‐Valverde, A., & Real, R. (2008) · Global Ecology and Biogeography · doi:10.1111/j.1466-8238.2007.00358.x · Cited by 3,499
Serial Evaluation of the SOFA Score to Predict Outcome in Critically Ill Patients
Ferreira, F. L. (2001) · JAMA · doi:10.1001/jama.286.14.1754 · Cited by 2,862
Selecting thresholds of occurrence in the prediction of species distributions
Liu, C., Berry, P. M., Dawson, T. P., & Pearson, R. G. (2005) · Ecography · doi:10.1111/j.0906-7590.2005.03957.x · Cited by 2,701
A Simple Generalisation of the Area Under the ROC Curve for Multiple Class Classification Problems
Hand, D. J., & Till, R. J. (2001) · Machine Learning · doi:10.1023/a:1010920819831 · Cited by 2,276
Greiner, M., Pfeiffer, D., & Smith, R. D. (2000) · Preventive Veterinary Medicine · doi:10.1016/s0167-5877(00)00115-x · Cited by 1,923
Protein biomarker discovery and validation: the long and uncertain path to clinical utility
Rifai, N., Gillette, M. A., & Carr, S. A. (2006) · Nature Biotechnology · doi:10.1038/nbt1235 · Cited by 1,867
Evaluating presence–absence models in ecology: the need to account for prevalence
Manel, S., Williams, H. C., & Ormerod, S. J. (2001) · Journal of Applied Ecology · doi:10.1046/j.1365-2664.2001.00647.x · Cited by 1,759
Crespo, M., Bosch, F., Villamor, N., Bellosillo, B., Colomer, D., Rozman, M., Marcé, S., López-Guillermo, A., Campo, E., & Montserrat, E. (2003) · New England Journal of Medicine · doi:10.1056/nejmoa023143 · Cited by 1,055
Statistical Classification Methods in Consumer Credit Scoring: A Review
Hand, D. J., & Henley, W. E. (1997) · Journal of the Royal Statistical Society Series A: Statistics in Society · doi:10.1111/j.1467-985x.1997.00078.x · Cited by 1,042
Revisiting biomarker discovery by plasma proteomics
Geyer, P. E., Holdt, L. M., Teupser, D., & Mann, M. (2017) · Molecular Systems Biology · doi:10.15252/msb.20156297 · Cited by 917
Defining an Optimal Cut-Point Value in ROC Analysis: An Alternative Approach
Unal, I. (2017) · Computational and Mathematical Methods in Medicine · doi:10.1155/2017/3762651 · Cited by 789
Neblett, R., Cohen, H., Choi, Y., Hartzell, M. M., Williams, M., Mayer, T. G., & Gatchel, R. J. (2013) · The Journal of Pain · doi:10.1016/j.jpain.2012.11.012 · Cited by 757
Bilici, M., Efe, H., Köroğlu, M. A., Uydu, H. A., Bekaroğlu, M., & Değer, O. (2001) · Journal of Affective Disorders · doi:10.1016/s0165-0327(00)00199-3 · Cited by 718
Variations of oral microbiota are associated with pancreatic diseases including pancreatic cancer
Farrell, J. J., Zhang, L., Zhou, H., Chia, D., Elashoff, D., Akin, D., Paster, B. J., Joshipura, K., & Wong, D. T. W. (2012) · Gut · doi:10.1136/gutjnl-2011-300784 · Cited by 662
Evaluating Intervention Effects in Single‐Case Research Designs
Vannest, K. J., & Ninci, J. (2015) · Journal of Counseling & Development · doi:10.1002/jcad.12038 · Cited by 665
Maes, M., Meltzer, H. Y., Bosmans, E., Bergmans, R., Vandoolaeghe, E., Ranjan, R., & Desnyder, R. (1995) · Journal of Affective Disorders · doi:10.1016/0165-0327(95)00028-l · Cited by 622
Kuramatsu, J. B., Gerner, S. T., Schellinger, P. D., Glahn, J., Endres, M., Sobesky, J., Flechsenhar, J., Neugebauer, H., Jüttler, E., Grau, A., et al. (2015) · JAMA · doi:10.1001/jama.2015.0846 · Cited by 568
Schiffman, M., Herrero, R., Hildesheim, A., Sherman, M. E., Bratti, M., Wacholder, S., Alfaro, M., Hutchinson, M., Morales, J., Greenberg, M. D., et al. (2000) · JAMA · doi:10.1001/jama.283.1.87 · Cited by 540
McCane, D. R., Hanson, R. L., Charles, M. A., Jacobsson, L. T. H., Pettitt, D. D., Bennett, P. H., & Knowler, W. C. (1994) · BMJ · doi:10.1136/bmj.308.6940.1323 · Cited by 484
Predictors of neonatal outcome in early-onset placental dysfunction
Baschat, A. A., Cosmi, E., Bilardo, C. M., Wolf, H., Berg, C., Rigano, S., Germer, U., Moyano, D., Turan, S., Hartung, J., et al. (2007) · Obstetrics & Gynecology · doi:10.1097/01.aog.0000253215.79121.75 · Cited by 485
Validation of a Korean Version of the Insomnia Severity Index
Cho, Y. W., Song, M. L., & Morinc, C. M. (2014) · Journal of Clinical Neurology · doi:10.3988/jcn.2014.10.3.210 · Cited by 472
Naccache, S. N., Federman, S., Veeraraghavan, N., Zaharia, M., Lee, D., Samayoa, E., Bouquet, J., Greninger, A. L., Luk, K.-C., Enge, B., et al. (2014) · Genome Research · doi:10.1101/gr.171934.113 · Cited by 460
Dehydration: Physiology, Assessment, and Performance Effects
Cheuvront, S. N., & Kenefick, R. W. (2014) · Comprehensive Physiology · doi:10.1002/cphy.c130017 · Cited by 461
Want to model a species niche? A step-by-step guideline on correlative ecological niche modelling
Sillero, N., Arenas-Castro, S., Enriquez‐Urzelai, U., Vale, C. G., Sousa-Guedes, D., Martínez-Freiría, F., Real, R., & Barbosa, A. M. (2021) · Ecological Modelling · doi:10.1016/j.ecolmodel.2021.109671 · Cited by 456
Grubin, C. E., Daniels, T., Toivola, B., Landin-Olsson, M., Hagopian, W. A., Li, L., Karlsen, A. E., Boel, E., Michelsen, B., & Lernmark, �. (1994) · Diabetologia · doi:10.1007/bf00408469 · Cited by 415
Tuinman, M. A., Gazendam‐Donofrio, S. M., & Hoekstra‐Weebers, J. E. (2008) · Cancer · doi:10.1002/cncr.23622 · Cited by 404
Maes, M., Lin, A.-H., Delmeire, L., Van Gastel, A., Kenis, G., De Jongh, R., & Bosmans, E. (1999) · Biological Psychiatry · doi:10.1016/s0006-3223(98)00131-0 · Cited by 387
Streckfus, C., & Bigler, L. (2002) · Oral Diseases · doi:10.1034/j.1601-0825.2002.1o834.x · Cited by 374
Biological variation and diagnostic accuracy of dehydration assessment markers
Cheuvront, S. N., Ely, B. R., Kenefick, R. W., & Sawka, M. N. (2010) · The American Journal of Clinical Nutrition · doi:10.3945/ajcn.2010.29490 · Cited by 367
Patel, V., Araya, R., Chowdhary, N., King, M., Kirkwood, B., Nayak, S., Simon, G., & Weiss, H. A. (2008) · Psychological Medicine · doi:10.1017/s0033291707002334 · Cited by 364
ROC Curves in Clinical Chemistry: Uses, Misuses, and Possible Solutions
Obuchowski, N. A., Lieber, M. L., & Wians, F. H. (2004) · Clinical Chemistry · doi:10.1373/clinchem.2004.031823 · Cited by 358
Screening for Abnormal Glucose Tolerance in Adolescents with Polycystic Ovary Syndrome
Palmert, M. R., Gordon, C. M., Kartashov, A. I., Legro, R. S., Emans, S. J., & Dunaif, A. (2002) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jcem.87.3.8305 · Cited by 354
Kanai, M., Matsubara, E., Isoe, K., Urakami, K., Nakashima, K., Arai, H., Sasaki, H., Abe, K., Iwatsubo, T., Kosaka, T., et al. (1998) · Annals of Neurology · doi:10.1002/ana.410440108 · Cited by 340
Lehmann, C., Koenig, T., Jelic, V., Prichep, L., John, R. E., Wahlund, L.-O., Dodge, Y., & Dierks, T. (2007) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2006.10.023 · Cited by 324
Obuchowski (2005) · doi:10.2214/ajr.184.2.01840364 · Cited by 321
Validation of the Insomnia Severity Index in Primary Care
Gagnon, C., Belanger, L., Ivers, H., & Morin, C. M. (2013) · The Journal of the American Board of Family Medicine · doi:10.3122/jabfm.2013.06.130064 · Cited by 319
Martin, A., Camacho, M., Portaels, F., & Palomino, J. C. (2003) · Antimicrobial Agents and Chemotherapy · doi:10.1128/aac.47.11.3616-3619.2003 · Cited by 306
Maes, M., Scharpé, S., Meltzer, H. Y., Okayli, G., Bosmans, E., D'Hondt, P., Vanden Bossche, B., & Cosyns, P. (1994) · Psychiatry Research · doi:10.1016/0165-1781(94)90003-5 · Cited by 302
Lubans, D. R., Hesketh, K., Cliff, D. P., Barnett, L. M., Salmon, J., Dollman, J., Morgan, P. J., Hills, A. P., & Hardy, L. L. (2011) · Obesity Reviews · doi:10.1111/j.1467-789x.2011.00896.x · Cited by 282
Maes, M., Vandoolaeghe, E., Neels, H., Demedts, P., Wauters, A., Meltzer, H. Y., Altamura, C., & Desnyder, R. (1997) · Biological Psychiatry · doi:10.1016/s0006-3223(96)00365-4 · Cited by 272
Halligan, S., Altman, D. G., & Mallett, S. (2015) · European Radiology · doi:10.1007/s00330-014-3487-0 · Cited by 255
Houdayer, C., Caux-Moncoutier, V., Krieger, S., Barrois, M., Bonnet, F., Bourdon, V., Bronner, M., Buisson, M., Coulet, F., Gaildrat, P., et al. (2012) · Human Mutation · doi:10.1002/humu.22101 · Cited by 239
Brain Tumor Classification Using Convolutional Neural Network
Das, S., Aranya, O. F. M. R. R., & Labiba, N. N. (2019) · 2019 1st International Conference on Advances in Science, Engineering and Robotics Technology (ICASERT) · doi:10.1109/icasert.2019.8934603 · Cited by 236
Retz-Junginger, P., Retz, W., Blocher, D., Stieglitz, R.-D., Georg, T., Supprian, T., Wender, P. H., & Rösler, M. (2003) · Der Nervenarzt · doi:10.1007/s00115-002-1447-4 · Cited by 233
Lower BMI cutoffs to define overweight and obesity in China
He, W., Li, Q., Yang, M., Jiao, J., Ma, X., Zhou, Y., Song, A., Heymsfield, S. B., Zhang, S., & Zhu, S. (2015) · Obesity · doi:10.1002/oby.20995 · Cited by 217
Vistisen, D., Andersen, G. S., Hansen, C. S., Hulman, A., Henriksen, J. E., Bech-Nielsen, H., & Jørgensen, M. E. (2016) · Circulation · doi:10.1161/circulationaha.115.018844 · Cited by 229
Motivations and Methods for Analyzing Pulsatile Hormone Secretion
Veldhuis, J. D., Keenan, D. M., & Pincus, S. M. (2008) · Endocrine Reviews · doi:10.1210/er.2008-0005 · Cited by 223
Cerniauskas, I., Winterer, J., de Jong, J. W., Lukacsovich, D., Yang, H., Khan, F., Peck, J. R., Obayashi, S. K., Lilascharoen, V., Lim, B. K., et al. (2019) · Neuron · doi:10.1016/j.neuron.2019.09.005 · Cited by 187
Fang, C.-K., Chang, M.-C., Chen, P.-J., Lin, C.-C., Chen, G.-S., Lin, J., Hsieh, R.-K., Chang, Y.-F., Chen, H.-W., Wu, C.-L., et al. (2014) · Supportive Care in Cancer · doi:10.1007/s00520-014-2290-4 · Cited by 211
Psychometric Evaluation of the PSQI in U.S. College Students
Dietch, J. R., Taylor, D. J., Sethi, K., Kelly, K., Bramoweth, A. D., & Roane, B. M. (2016) · Journal of Clinical Sleep Medicine · doi:10.5664/jcsm.6050 · Cited by 209
Mewton, L., Kessler, R. C., Slade, T., Hobbs, M. J., Brownhill, L., Birrell, L., Tonks, Z., Teesson, M., Newton, N., Chapman, C., et al. (2016) · Psychological Assessment · doi:10.1037/pas0000239 · Cited by 196
Maes, M., Lin, A., Bonacccorso, S., Van Hunsel, F., GASTEL, A. V., Delmeire, L., Biondi, M., Bosmans, E., Kenis, G., & Scharpé, S. (1998) · Acta Psychiatrica Scandinavica · doi:10.1111/j.1600-0447.1998.tb10092.x · Cited by 204
Maessen, M. F. H., Eijsvogels, T. M. H., Verheggen, R. J. H. M., Hopman, M. T. E., Verbeek, A. L. M., & Vegt, F. D. (2014) · PLoS ONE · doi:10.1371/journal.pone.0107212 · Cited by 203
van Steenbergen-Weijenburg, K. M., de Vroege, L., Ploeger, R. R., Brals, J. W., Vloedbeld, M. G., Veneman, T. F., Hakkaart-van Roijen, L., Rutten, F. F., Beekman, A. T., & van der Feltz-Cornelis, C. M. (2010) · BMC Health Services Research · doi:10.1186/1472-6963-10-235 · Cited by 200
Schaefer, A. L., Cook, N. J., Church, J. S., Basarab, J., Perry, B., Miller, C., & Tong, A. K. W. (2007) · Research in Veterinary Science · doi:10.1016/j.rvsc.2007.01.008 · Cited by 196
Out-of-Hemodialysis-Unit Blood Pressure Is a Superior Determinant of Left Ventricular Hypertrophy
Agarwal, R., Brim, N. J., Mahenthiran, J., Andersen, M. J., & Saha, C. (2006) · Hypertension · doi:10.1161/01.hyp.0000196279.29758.f4 · Cited by 181
Stensrud, S., Myklebust, G., Kristianslund, E., Bahr, R., & Krosshaug, T. (2011) · British Journal of Sports Medicine · doi:10.1136/bjsm.2010.078287 · Cited by 175
Home blood pressure monitoring improves the diagnosis of hypertension in hemodialysis patients
Agarwal, R., Andersen, M. J., Bishu, K., & Saha, C. (2006) · Kidney International · doi:10.1038/sj.ki.5000145 · Cited by 175
The Intolerance of Uncertainty Scale for Children: A psychometric evaluation.
Comer, J. S., Roy, A. K., Furr, J. M., Gotimer, K., Beidas, R. S., Dugas, M. J., & Kendall, P. C. (2009) · Psychological Assessment · doi:10.1037/a0016719 · Cited by 162
Predicting probable Alzheimer's disease using linguistic deficits and biomarkers
Orimaye, S. O., Wong, J. S.-M., Golden, K. J., Wong, C. P., & Soyiri, I. N. (2017) · BMC Bioinformatics · doi:10.1186/s12859-016-1456-0 · Cited by 158
Shah, S. M. S., Batool, S., Khan, I., Ashraf, M. U., Abbas, S. H., & Hussain, S. A. (2017) · Physica A: Statistical Mechanics and its Applications · doi:10.1016/j.physa.2017.04.113 · Cited by 150
Scott, W., Wideman, T. H., & Sullivan, M. J. L. (2014) · The Clinical Journal of Pain · doi:10.1097/ajp.0b013e31828eee6c · Cited by 155
Tremor stability index: a new tool for differential diagnosis in tremor syndromes
di Biase, L., Brittain, J.-S., Shah, S. A., Pedrosa, D. J., Cagnan, H., Mathy, A., Chen, C. C., Martín-Rodríguez, J. F., Mir, P., Timmerman, L., et al. (2017) · Brain · doi:10.1093/brain/awx104 · Cited by 140
The psychometric properties of the MASC in a pediatric psychiatric sample
Rynn, M. A., Barber, J. P., Khalid-Khan, S., Siqueland, L., Dembiski, M., McCarthy, K. S., & Gallop, R. (2006) · Journal of Anxiety Disorders · doi:10.1016/j.janxdis.2005.01.004 · Cited by 138
Philip, P., Micoulaud-Franchi, J.-A., Sagaspe, P., Sevin, E. D., Olive, J., Bioulac, S., & Sauteraud, A. (2017) · Scientific Reports · doi:10.1038/srep42656 · Cited by 128
Villar, J., Martín-Rodríguez, C., Domínguez-Berrot, A. M., Fernández, L., Ferrando, C., Soler, J. A., Díaz-Lamas, A. M., González-Higueras, E., Nogales, L., Ambrós, A., et al. (2017) · Critical Care Medicine · doi:10.1097/ccm.0000000000002330 · Cited by 127
Greco, E., Gupta, R., Syngelaki, A., Poon, L. C. Y., & Nicolaides, K. H. (2012) · Fetal Diagnosis and Therapy · doi:10.1159/000335686 · Cited by 126
Yeo, W., Chan, S. L., Mo, F. K., Chu, C. M., Hui, J. W., Tong, J. H., Chan, A. W., Koh, J., Hui, E. P., Loong, H., et al. (2015) · BMC Cancer · doi:10.1186/s12885-015-1334-6 · Cited by 125
Brooks, S. J., Krulewicz, S. P., & Kutcher, S. (2003) · Journal of Child and Adolescent Psychopharmacology · doi:10.1089/104454603322572679 · Cited by 120
Carella, C., Mazziotti, G., Sorvillo, F., Piscopo, M., Cioffi, M., Pilla, P., Nersita, R., Iorio, S., Amato, G., Braverman, L. E., et al. (2006) · Thyroid · doi:10.1089/thy.2006.16.295 · Cited by 119
Härter, K. R. (2001) · Disability and Rehabilitation · doi:10.1080/09638280110062176 · Cited by 113
Poon, L. C. Y., Karagiannis, G., Staboulidou, I., Shafiei, A., & Nicolaides, K. H. (2011) · Prenatal Diagnosis · doi:10.1002/pd.2520 · Cited by 115
Improving the Positive Predictive Value of Screening for Developmental Language Disorder
Klee, T., Pearce, K., & Carson, D. K. (2000) · Journal of Speech, Language, and Hearing Research · doi:10.1044/jslhr.4304.821 · Cited by 114
Søreide, K., Kørner, H., & Søreide, J. A. (2011) · Annals of Surgery · doi:10.1097/sla.0b013e318204a892 · Cited by 109
Hooper, L., Abdelhamid, A., Ali, A., Bunn, D. K., Jennings, A., John, W. G., Kerry, S., Lindner, G., Pfortmueller, C. A., Sjöstrand, F., et al. (2015) · BMJ Open · doi:10.1136/bmjopen-2015-008846 · Cited by 109
Shibahara, H., Obara, H., Ayustawati, Hirano, Y., Suzuki, T., Ohno, A., Takamizawa, S., & Suzuki, M. (2004) · International Journal of Andrology · doi:10.1111/j.0105-6263.2004.00437.x · Cited by 92
Garcia, F. D., Grigioni, S., Allais, E., Houy-Durand, E., Thibaut, F., & Déchelotte, P. (2011) · Clinical Nutrition · doi:10.1016/j.clnu.2010.09.007 · Cited by 91
Nobukawa, S., Yamanishi, T., Kasakawa, S., Nishimura, H., Kikuchi, M., & Takahashi, T. (2020) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2020.00255 · Cited by 89
Suliman, A. M., Smith, T. P., Labib, M., Fiad, T. M., & McKenna, T. J. (2002) · Clinical Endocrinology · doi:10.1046/j.1365-2265.2002.01509.x · Cited by 75
Distinguishing the Central Drive to Tremor in Parkinson’s Disease and Essential Tremor
Brittain, J.-S., Cagnan, H., Mehta, A. R., Saifee, T. A., Edwards, M. J., & Brown, P. (2015) · The Journal of Neuroscience · doi:10.1523/jneurosci.3768-14.2015 · Cited by 77
Mental health screening in addiction, corrections and social service settings: Validating the MMS
Alexander, M. J., Haugland, G., Lin, S. P., Bertollo, D. N., & McCorry, F. A. (2008) · International Journal of Mental Health and Addiction · doi:10.1007/s11469-007-9100-x · Cited by 71
Dipstick urinalysis and the accuracy of the clinical diagnosis of urinary tract infection
Sultana, R. V., Zalstein, S., Cameron, P., & Campbell, D. (2001) · The Journal of Emergency Medicine · doi:10.1016/s0736-4679(00)00290-0 · Cited by 72
Development of the Spence Children’s Anxiety Scale - Short Version (SCAS-S)
Ahlen, J., Vigerland, S., & Ghaderi, A. (2018) · Journal of Psychopathology and Behavioral Assessment · doi:10.1007/s10862-017-9637-3 · Cited by 69
van Doormaal, J. J., van der Veer, E., van Voorst Vader, P. C., Kluin, P. M., Mulder, A. B., van der Heide, S., Arends, S., Kluin‐Nelemans, J. C., Oude Elberink, J. N. G., & de Monchy, J. G. R. (2012) · Allergy · doi:10.1111/j.1398-9995.2012.02809.x · Cited by 63
Tu, Y.-L., Chang, S.-W., Tsai, H.-J., Chen, L.-C., Lee, W.-I., Hua, M.-C., Cheng, J.-H., Ou, L.-S., Yeh, K.-W., Huang, J.-L., et al. (2013) · PLoS ONE · doi:10.1371/journal.pone.0080996 · Cited by 65
Bohland, J. W., Saperstein, S., Pereira, F., Rapin, J., & Grady, L. (2012) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2012.00078 · Cited by 64
Reynolds Adolescent Depression Scale-second edition: a reliable and useful instrument
Osman, A., Gutierrez, P. M., Bagge, C. L., Fang, Q., & Emmerich, A. (2010) · Journal of Clinical Psychology · doi:10.1002/jclp.20727 · Cited by 62
Tzani, P., Aiello, M., Elia, D., Boracchia, L., Marangio, E., Olivieri, D., Clini, E., & Chetta, A. (2011) · Respiratory Research · doi:10.1186/1465-9921-12-150 · Cited by 62
Evans, R., Thirlwall, K., Cooper, P., & Creswell, C. (2017) · Psychological Assessment · doi:10.1037/pas0000375 · Cited by 58
Effect of carbohydrate feeding on the bone metabolic response to running
Sale, C., Varley, I., Jones, T. W., James, R. M., Tang, J. C. Y., Fraser, W. D., & Greeves, J. P. (2015) · Journal of Applied Physiology · doi:10.1152/japplphysiol.00241.2015 · Cited by 57
Oxygen saturation regularity analysis in the diagnosis of obstructive sleep apnea
del Campo, F., Hornero, R., Zamarrón, C., Abasolo, D. E., & Álvarez, D. (2006) · Artificial Intelligence in Medicine · doi:10.1016/j.artmed.2005.10.005 · Cited by 56
Roy, N., Mazin, A., & Awan, S. N. (2014) · The Laryngoscope · doi:10.1002/lary.24362 · Cited by 54
Monticone, M., Ambrosini, E., Rocca, B., Foti, C., & Ferrante, S. (2016) · European Spine Journal · doi:10.1007/s00586-016-4682-2 · Cited by 52
Multimodal Hippocampal Subfield Grading For Alzheimer’s Disease Classification
Hett, K., Ta, V.-T., Catheline, G., Tourdias, T., Manjón, J. V., Coupé, P., Initiative, A. D. N., Weiner, M. W., Aisen, P., Petersen, R., et al. (2019) · Scientific Reports · doi:10.1038/s41598-019-49970-9 · Cited by 49
Jokinen, J., Nordström, A.-L., & Nordström, P. (2008) · Journal of Affective Disorders · doi:10.1016/j.jad.2007.06.008 · Cited by 45
Metadata
- Authors
- Zweig, M. H., & Campbell, G.
- Venue
- Clinical Chemistry
- Publisher
- Oxford University Press (OUP)
- Published
- 1993-04-01
- Volume
- 39
- Issue
- 4
- Pages
- 561-577
- ISSN
- 0009-9147 (ISSN-L)
- 1530-8561
- OpenAlex
- W2104960492
- Cited by
- 6,569
- References
- 3
- FWCI
- 53.71
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
