A readers' guide to the interpretation of diagnostic test properties: clinical example of sepsis

Measuring the Accuracy of Diagnostic Systems

Swets, J. A. (1988) · Science · doi:10.1126/science.3287615 · Cited by 10,058

A method of comparing the areas under receiver operating characteristic curves derived from the same cases

Hanley, J. A., & McNeil, B. J. (1983) · Radiology · doi:10.1148/radiology.148.3.6878708 · Cited by 7,016

Users' Guides to the Medical Literature

Guyatt, G. H. (1993) · JAMA · doi:10.1001/jama.270.17.2096 · Cited by 3,083

Users' Guides to the Medical Literature

Jaeschke, R. (1994) · JAMA · doi:10.1001/jama.271.9.703 · Cited by 2,688

Empirical evidence of design-related bias in studies of diagnostic tests.

Lijmer, J. G. (1999) · JAMA · doi:10.1001/jama.282.11.1061 · Cited by 1,861

Clinical decision analysis

Mumber, M. P. (2005) · CRC Press eBooks · doi:10.1201/9780203088319-19 · Cited by 1,584

Clinical Decision Analysis

Fischhoff, B. (1980) · Operations Research · doi:10.1287/opre.28.1.28 · Cited by 1,423

The Threshold Approach to Clinical Decision Making

Pauker, S. G., & Kassirer, J. P. (1980) · New England Journal of Medicine · doi:10.1056/nejm198005153022003 · Cited by 1,371

Users' Guides to the Medical Literature

Jaeschke, R. (1994) · JAMA · doi:10.1001/jama.271.5.389 · Cited by 1,174

Nomogram for Bayes's Theorem

(1975) · New England Journal of Medicine · doi:10.1056/nejm197507312930513 · Cited by 1,017

The Cutoff Point and Diagnostic Accuracy of the Voice Handicap Index in Cantonese-Speaking Population

Ng, E., Law, T. K. T., Tang, E. C.-H., Ho, F. N.-Y., Tong, M. C. F., & Lee, K. (2020) · Journal of Voice · doi:10.1016/j.jvoice.2020.09.021 · Cited by 14

Perioperative fluids and complications after pancreatoduodenectomy within an enhanced recovery pathway

Gilgien, J., Hübner, M., Halkic, N., Demartines, N., & Roulin, D. (2020) · Scientific Reports · doi:10.1038/s41598-020-74907-y · Cited by 14

Gray matter volumes discriminate cognitively impaired and unimpaired people with HIV

Schantell, M. D., Taylor, B. K., Lew, B. J., O’Neill, J., May, P. E., Swindells, S., & Wilson, T. W. (2021) · NeuroImage Clinical · doi:10.1016/j.nicl.2021.102775 · Cited by 14

Development of a Machine Learning Algorithm for Prediction of Complications and Unplanned Readmission Following Primary Anatomic Total Shoulder Replacements

Devana, S. K., Shah, A. A., Lee, C., Jensen, A. R., Cheung, E., van der Schaar, M., & SooHoo, N. F. (2022) · Journal of Shoulder and Elbow Arthroplasty · doi:10.1177/24715492221075444 · Cited by 14

Assessing Adolescent Personality Disorders With the Shedler-Westen Assessment Procedure for Adolescents

DeFife, J. A., Malone, J. C., Dilallo, J. J., & Westen, D. (2013) · Clinical Psychology Science and Practice · doi:10.1037/h0101720 · Cited by 14

Can Dental Students Be Taught to Use Dental Radiographs for Osteoporosis Screening?

Shintaku, W. H., Enciso, R., Covington, J. S., & Migliorati, C. A. (2013) · Journal of Dental Education · doi:10.1002/j.0022-0337.2013.77.5.tb05508.x · Cited by 14

Gait analysis of patients with knee osteoarthritis by using elevation angle: confirmation of the planar law and analysis of angular difference in the approximate plane

Ishikawa, Y., An, Q., Nakagawa, J., Oka, H., Yasui, T., Tojima, M., Inokuchi, H., Haga, N., Yamakawa, H., Tamura, Y., et al. (2016) · Advanced Robotics · doi:10.1080/01691864.2016.1229217 · Cited by 14

Receiver Operating Characteristic curve analysis determines association of individual potato foliage volatiles with onion thrips preference, cultivar and plant age

Wilson, C. R., Davies, N. W., Corkrey, R., Wilson, A. J., Mathews, A., & Westmore, G. (2017) · PLoS ONE · doi:10.1371/journal.pone.0181831 · Cited by 14

The Inventory of Depressive Symptomatology Self Report (IDS-SR): Psychometric properties of the Indonesian version

Arjadi, R., Nauta, M. H., Utoyo, D. B., & Bockting, C. (2017) · PLoS ONE · doi:10.1371/journal.pone.0187009 · Cited by 14

Empirical typology of adolescent personality organization

Biberdzic, M., Ensink, K., Normandin, L., & Clarkin, J. F. (2018) · Journal of Adolescence · doi:10.1016/j.adolescence.2018.04.004 · Cited by 16

A pedestrian serious injury risk prediction method based on posted speed limit

Nishimoto, T., Kubota, K., & Ponte, G. (2019) · Accident Analysis & Prevention · doi:10.1016/j.aap.2019.04.021 · Cited by 14

The use of magnetic resonance imaging in differential diagnosis of allergic fungal sinusitis and eosinophilic mucin rhinosinusitis

Meng, Y., Zhang, L., Piao, Y., Lou, H., Wang, K., & Wang, C. (2019) · Journal of Thoracic Disease · doi:10.21037/jtd.2019.07.26 · Cited by 14

Preoperative CT for prediction of local recurrence after curettage of giant cell tumor of bone

Zhou, L., Lin, S., Jin, H., Zhang, Z., Zhang, C., & Yuan, T. (2021) · Journal of bone oncology · doi:10.1016/j.jbo.2021.100366 · Cited by 14

Clinical Importance of Eosinophil Count in Nasal Fluid in Patients with Allergic and Non-Allergic Rhinitis

Lorenzo, G. D., Mansueto, P., Pacor, M. L., Martinelli, N., Rizzo, M., Ditta, V., Leto‐Barone, M. S., D’Alcamo, A., Politi, D., Pepe, I., et al. (2009) · International Journal of Immunopathology and Pharmacology · doi:10.1177/039463200902200424 · Cited by 14

Multiple logistic regression model to predict bile leak associated with subtotal cholecystectomy

Lunevičius, R., & Nzenwa, I. C. (2023) · Surgical Endoscopy · doi:10.1007/s00464-023-10049-2 · Cited by 13

Prognostic models for surgical-site infection in gastrointestinal surgery: systematic review

McLean, K. A., Goel, T., Lawday, S., Riad, A., Simoes, J. F. F., Knight, S. R., Ghosh, D., Glasbey, J. C., Bhangu, A. A., & Harrison, E. M. (2023) · British journal of surgery · doi:10.1093/bjs/znad187 · Cited by 18

The generalizability of the Risk Matrix 2000: On model shrinkage and the misinterpretation of the area under the curve.

Cooke, D. J., & Michie, C. (2013) · Journal of Threat Assessment and Management · doi:10.1037/tam0000004 · Cited by 13

Sarcopenia and physical activity in older male cardiac patients

Izawa, K. P., Watanabe, S., Oka, K., Kasahara, Y., Morio, Y., Hiraki, K., Hirano, Y., Omori, Y., Suzuki, N., Kida, K., et al. (2016) · International Journal of Cardiology · doi:10.1016/j.ijcard.2016.07.167 · Cited by 13

Identifying Asthma Exacerbation-Related Emergency Department Visit Using Electronic Medical Record and Claims Data

Sundaresan, A. S., Schneider, G., Reynolds, J., & Kirchner, H. L. (2018) · Applied Clinical Informatics · doi:10.1055/s-0038-1666994 · Cited by 13

Antibody response against Mycobacterium avium complex in cystic fibrosis patients measured by a novel IgG ELISA test

Ravnholt, C., Qvist, T., Kolpen, M., Pressler, T., Skov, M., & Høiby, N. (2018) · Journal of Cystic Fibrosis · doi:10.1016/j.jcf.2018.11.011 · Cited by 13

Validation of Addiction Severity Index (ASI) for Assessment of Psychiatric Comorbidity in Multi-Site Randomized Controlled Trials

Susukida, R., Mojtabai, R., & Amin‐Esmaeili, M. (2020) · Journal of Dual Diagnosis · doi:10.1080/15504263.2020.1741755 · Cited by 13

Informative value of referral letters from general practice for child and adolescent mental healthcare

Aydın, S., Crone, M. R., Siebelink, B. M., Numans, M. E., Vermeiren, R. R. J. M., & Westenberg, P. M. (2021) · European Child & Adolescent Psychiatry · doi:10.1007/s00787-021-01859-7 · Cited by 13

Concurrent wasting and stunting among children 6–59 months: an analysis using district-level survey data in Mozambique

Zaba, T., Conkle, J., Nyawo, M., Foote, D., & Myatt, M. A. (2022) · BMC Nutrition · doi:10.1186/s40795-022-00508-9 · Cited by 13

Genetic variation influences the risk of bleeding after cardiac surgery: novel associations and validation of previous findings

Greiff, G., Pleym, H., Stenseth, R., Wahba, A., & Videm, V. (2015) · Acta Anaesthesiologica Scandinavica · doi:10.1111/aas.12504 · Cited by 13

Nursing home-acquired pneumonia presenting at the emergency department

Pereira, R., de Oliveira, S. P., & Almeida, A. (2016) · Internal and Emergency Medicine · doi:10.1007/s11739-016-1412-z · Cited by 13

Reliability, Validity, and Clinical Utility of the Dominic Interactive for Adolescents–Revised

Bergeron, L., Smolla, N., Berthiaume, C., Renaud, J., Breton, J., St‐Georges, M., Morin, P., Zavaglia, E., & Labelle, R. J. (2016) · The Canadian Journal of Psychiatry · doi:10.1177/0706743716670129 · Cited by 13

Dyskinesia and FAB score predict future falling in Parkinson's disease

Lindholm, B., Eek, F., Skogar, Ö., & Hansson, E. E. (2019) · Acta Neurologica Scandinavica · doi:10.1111/ane.13084 · Cited by 13

Diagnostic Value of CRP and Serum WBC Count during Septic Two-Stage Revision of Total Hip Arthroplasties

Mederake, M., Hofmann, U. K., Benda, S., Schuster, P., & Fink, B. (2022) · Antibiotics · doi:10.3390/antibiotics11081098 · Cited by 13

Association between umbilical cord artery pCO 2 and the Apgar score; elevated levels of pCO 2 may be beneficial for neonatal vitality after moderate acidemia

Kro, G. B., Yli, B. M., Rasmussen, S., Norén, H., Amer‐Wåhlin, I., Rosén, K. G., Stray‐Pedersen, B., & Saugstad, O. D. (2013) · Acta Obstetricia Et Gynecologica Scandinavica · doi:10.1111/aogs.12090 · Cited by 13

Antral follicle count at down-regulation and prediction of poor ovarian response

Khairy, M., Clough, A., El‐Toukhy, T., Coomarasamy, A., & Khalaf, Y. (2008) · Reproductive BioMedicine Online · doi:10.1016/s1472-6483(10)60237-4 · Cited by 13

The IL-6 −174G/C polymorphism and renal scarring in children with first acute pyelonephritis

Spasojević, B., Živković, M., Stanković, A., Stojković, L., & Kostić, M. (2010) · Pediatric Nephrology · doi:10.1007/s00467-010-1587-x · Cited by 13

The Edmonton Symptom Assessment System: Poor performance as screener for major depression in patients with incurable cancer

Brenne, E., Loge, J. H., Lie, H. C., Hjermstad, M. J., Fayers, P. M., & Kaasa, S. (2016) · Palliative Medicine · doi:10.1177/0269216315620082 · Cited by 13

Predicting Depression in Patients With Knee Osteoarthritis Using Machine Learning: Model Development and Validation Study

Nowinka, Z., Alagha, M. A., Mahmoud, K., & Jones, G. G. (2022) · JMIR Formative Research · doi:10.2196/36130 · Cited by 13

Comprehension of irony in autistic children: The role of theory of mind and executive function

Song, Y., Nie, Z., & Shan, J. (2023) · Autism Research · doi:10.1002/aur.3051 · Cited by 15

Prediction of preterm birth in multiparous women using logistic regression and machine learning approaches

Belaghi, R. A. (2024) · Scientific Reports · doi:10.1038/s41598-024-60097-4 · Cited by 12

Can we rely on the combination of serological tests and frozen sections at the time of reimplantation for two-stage exchange hip arthroplasty in patients with a “dry tap”?

Xu, C., Chai, W., & Chen, J. (2019) · Journal of Orthopaedic Surgery and Research · doi:10.1186/s13018-019-1223-9 · Cited by 12

Venous Thromboembolism in a Single Korean Trauma Center: Incidence, Risk Factors, and Assessing the Validity of VTE Diagnostic Tools

Boo, S., Oh, H., Hwang, K., Jung, K., & Moon, J. (2021) · Yonsei Medical Journal · doi:10.3349/ymj.2021.62.6.520 · Cited by 12

Small internal jugular veins with restricted outflow are associated with severe multiple sclerosis: a sonographer-blinded, case–control ultrasound study

Krsmanović, Ž., Živković, M., Lepić, T., Stanković, A., Raičević, R., & Dinčić, E. (2013) · BMC Neurology · doi:10.1186/1471-2377-13-90 · Cited by 12

Psychometric Properties and Clinical Usefulness of the Youth Self-Report DSM-Oriented Scales: A Field Study among Detained Male Adolescents

Colins, O. F. (2016) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph13090932 · Cited by 12

Predictive Bayesian Network Model Using Electronic Patient Records for Prevention of Hospital-Acquired Pressure Ulcers

Cho, I., & Chung, E. (2011) · Journal of Korean Academy of Nursing · doi:10.4040/jkan.2011.41.3.423 · Cited by 12

Pharmacogenetic association study of 30 genes with phenobarbital drug response in epileptic dogs

Kennerly, E., Idaghdour, Y., Olby, N. J., Muñana, K. R., & Gibson, G. C. (2009) · Pharmacogenetics and Genomics · doi:10.1097/fpc.0b013e3283307cba · Cited by 13

C-Reactive Protein and Procalcitonin as Markers of Infection, Inflammatory Response, and Sepsis

Sierra, R. (2007) · Clinical Pulmonary Medicine · doi:10.1097/cpm.0b013e3180555bbe · Cited by 12

The relation of standardized mental health screening and categorical assessment in detained male adolescents

Colins, O. F., Grisso, T., Mulder, E. A., & Vermeiren, R. R. J. M. (2014) · European Child & Adolescent Psychiatry · doi:10.1007/s00787-014-0584-1 · Cited by 11

Clinical Utility of the Parent-Report Version of the Strengths and Difficulties Questionnaire (SDQ) in Latvian Child and Adolescent Psychiatry Practice

Bezborodovs, N., Kočāne, A., Rancāns, E., & Villeruša, A. (2022) · Medicina · doi:10.3390/medicina58111599 · Cited by 12

Qnox index for quantification of intraoperative nociception and analgesia: a prospective single-centre validation study

Kong, H., Ma, D.-D., Ma, J., Zhang, Y.-X., Zhang, H., & Wang, D. (2025) · British Journal of Anaesthesia · doi:10.1016/j.bja.2024.10.051 · Cited by 11

Screening Accuracy of the Brief Infant Toddler Social-Emotional Assessment to Identify Autism Spectrum Disorder in Toddlers Born at Less Than 30 Weeks’ Gestation

Boone, K. M., Brown, A. K., & Keim, S. A. (2017) · Child Psychiatry & Human Development · doi:10.1007/s10578-017-0768-2 · Cited by 12

Can the calf-raise senior test predict functional fitness in elderly people? A validation study using electromyography, kinematics and strength tests

André, H., Carnide, F., Moço, A., Valamatos, M. J., Ramalho, F., Santos‐Rocha, R., & Veloso, A. (2018) · Physical Therapy in Sport · doi:10.1016/j.ptsp.2018.05.012 · Cited by 14

Neurobehavioral symptom validity and performance validity in veterans: Evidence for distinct outcomes across data types

Bomyea, J. A., Jurick, S. M., Keller, A. V., Hays, C. C., Twamley, E. W., & Jak, A. J. (2018) · Applied Neuropsychology Adult · doi:10.1080/23279095.2018.1480484 · Cited by 11

A Risk Calculator for the Prediction of C5 Nerve Root Palsy After Instrumented Cervical Fusion

Shah, A. A., Devana, S. K., Lee, C., Bugarin, A., Hong, M. K., Upfill-Brown, A. M., Blumstein, G. W., Lord, E. L., Shamie, A. N., van der Schaar, M., et al. (2022) · World Neurosurgery · doi:10.1016/j.wneu.2022.07.082 · Cited by 11

Diagnostic value of soluble biomarkers for parapneumonic pleural effusion

Cao, X., Zheng, W., & Hu, Z.-D. (2023) · Critical Reviews in Clinical Laboratory Sciences · doi:10.1080/10408363.2022.2158779 · Cited by 11

Identification of Inflammatory Endotypes by Clinical Characteristics and Nasal Secretion Biomarkers in Chronic Rhinosinusitis with Nasal Polyps

Guo, C., Lu, R.-Y., Wang, C., Zhao, J.-F., Li, P., Liu, H.-C., Liao, B., & Liu, Z. (2023) · International Archives of Allergy and Immunology · doi:10.1159/000530193 · Cited by 11

The role of Fibroscan in predicting the presence of varices in patients with cirrhosis

Al-hamoudi, W., Awny, A., Helmy, A., Anil, S., Khamis, N., Arafah, M., Alswat, K., Suwefy, Y. M., Sanai, F. M., Faleh, F. A., et al. (2015) · European Journal of Gastroenterology & Hepatology · doi:10.1097/meg.0000000000000432 · Cited by 11

Computed Tomography Score an Excellent Marker: Differentiates Eosinophilic and Non-eosinophilic Variants of Chronic Rhinosinusitis with Nasal Polyp

Rai, G., Roy, P., Gupta, N., Sharma, S., Dar, S. A., Ansari, M. A., Ramachandran, V. G., & Das, S. (2017) · Indian Journal of Otolaryngology and Head & Neck Surgery · doi:10.1007/s12070-017-1154-x · Cited by 11

Conventional Magnetic Resonance Imaging in the Diagnosis of Parkinsonian Disorders: A Meta‐Analysis

Lee, W. (2020) · Movement Disorders Clinical Practice · doi:10.1002/mdc3.13070 · Cited by 11

Predictive performance of thyromental height for difficult laryngoscopies in adults: a systematic review and meta-analysis

de Carvalho, C. C., Neto, J. M. D. S., & de Orange, F. V. A. (2021) · Brazilian Journal of Anesthesiology (English Edition) · doi:10.1016/j.bjane.2021.06.015 · Cited by 11

Machine Learning–Based Personalized Prediction of Hepatocellular Carcinoma Recurrence After Radiofrequency Ablation

Sato, M., Tateishi, R., Moriyama, M., Fukumoto, T., Yamada, T., Nakagomi, R., Kinoshita, M. N., Nakatsuka, T., Minami, T., Uchino, K., et al. (2022) · Gastro Hep Advances · doi:10.1016/j.gastha.2021.09.003 · Cited by 11

Utility of Green's Word Memory Test Free Recall Subtest as a Measure of Verbal Memory: Initial Evidence from a Temporal Lobe Epilepsy Clinical Sample

Soble, J. R., Osborn, K. E., Mattingly, M., Vale, F. Ĺ., Benbadis, S. R., Rodgers-Neame, N. T., & Schoenberg, M. R. (2015) · Archives of Clinical Neuropsychology · doi:10.1093/arclin/acv084 · Cited by 11

Comparison of oral hypofunction tests and determination of reference values for a subjective masticatory function test

Uchida, Y., Sato, Y., Kitagawa, N., Furuya, J., Osawa, T., Isobe, A., Terazawa, M., Hatanaka, Y., & Shichita, T. (2022) · BMC Oral Health · doi:10.1186/s12903-022-02252-9 · Cited by 10

Utility of the NIH Toolbox Cognition Battery in middle to older aged adults with longstanding type 1 diabetes: The DCCT/EDIC study

Chaytor, N. S., Trapani, V. R., Braffett, B. H., Fonseca, L. M., Lorenzi, G. M., Gubitosi‐Klug, R., HITT, S. M., Farrell, K., Jacobson, A. M., & Ryan, C. M. (2023) · The Clinical Neuropsychologist · doi:10.1080/13854046.2023.2266876 · Cited by 10

Predictive value of dynamic arterial elastance for vasopressor withdrawal: a systematic review and meta-analysis

Sánchez, J. I. A., Salazar-Ruiz, S., Caicedo-Ruiz, J. D., Fernández, J. J. D., Bolívar, Y. R. C., Hernández, F. L. C., Mora‐Salamanca, A. F., Montañez-Nariño, A. V., Stozitzky-Ríos, M. V., Santacruz-Herrera, C., et al. (2024) · Annals of Intensive Care · doi:10.1186/s13613-024-01345-8 · Cited by 10

Reliability and validity of facial expression recognition in the screening of generalized anxiety disorder

Ren, X., Su, S., Jiang, W., Wang, Y., Yao, J., Su, Y., Wu, Y., Tao, J., Peng, Y., & Qiu, J. (2024) · Journal of Affective Disorders · doi:10.1016/j.jad.2024.10.022 · Cited by 10

Changes in pulse pressure variation induced by passive leg raising test to predict preload responsiveness in mechanically ventilated patients with low tidal volume in ICU: a systematic review and meta-analysis

Mallat, J., Siuba, M., Arab, O. A., Kovačević, P., Ismail, K., Duggal, A., & Guinot, P. (2025) · Critical Care · doi:10.1186/s13054-024-05238-x · Cited by 13

Effects of Sampling Frequency on Human Activity Recognition with Machine Learning Aiming at Clinical Applications

Yamane, T., Kimura, M., & Morita, M. (2025) · Sensors · doi:10.3390/s25123780 · Cited by 13

Hip Abductor Strength and Lower Limb Load on Nonoperating Predict Functional Mobility in Women Patients With Total Hip Arthroplasty

Murao, M., Nankaku, M., Hamada, R., Kawano, T., Goto, K., Kuroda, Y., Ikeguchi, R., & Matsuda, S. (2020) · American Journal of Physical Medicine & Rehabilitation · doi:10.1097/phm.0000000000001523 · Cited by 10

Detection of congestive heart failure by mitral annular displacement in cats with hypertrophic cardiomyopathy – concordance between tissue Doppler imaging–derived tissue tracking and M-mode

Bach, M. B. T., Grevsen, J. R., Kiely, M. A. B., Willesen, J. L., & Koch, J. (2021) · Journal of Veterinary Cardiology · doi:10.1016/j.jvc.2021.06.003 · Cited by 10

The utility of parent-report screening tools in differentiating autism versus attention-deficit/hyperactivity disorder in school-age children

Guttentag, S., Bishop, S. L., Doggett, R. A., Shalev, R. A., Kaplan, M., Dyson, M. W., Cohen, M. T., Lord, C., & Martino, A. D. (2021) · Autism · doi:10.1177/13623613211030071 · Cited by 11

Evaluation of the ability of the C-reactive protein-to-albumin ratio to predict short-term mortality in patients with COVID-19

Özdemir, S., & Algın, A. (2021) · Journal of Clinical Medicine of Kazakhstan · doi:10.23950/jcmk/11324 · Cited by 10

Psychometric properties of the EQ-5D-3L in South Australia: a multi-method non-preference-based validation study

Zakershahrak, M., Santiago, P. H. R., Sethi, S., Haag, D. G., Jamieson, L., & Brennan, D. S. (2022) · Current Medical Research and Opinion · doi:10.1080/03007995.2022.2031941 · Cited by 10

Development and External Validation of a Risk Calculator for Prediction of Major Complications and Readmission After Anterior Cervical Discectomy and Fusion

Shah, A. A., Devana, S. K., Lee, C. H., Olson, T. E., Upfill-Brown, A. M., Sheppard, W. L., Lord, E. L., Shamie, A. N., van der Schaar, M., SooHoo, N. F., et al. (2022) · Spine · doi:10.1097/brs.0000000000004531 · Cited by 10

Web-based screening for Panic Disorder: Validity of a single-item instrument

Oromendia, P., Bonillo, A., & Molinuevo, B. (2015) · Journal of Affective Disorders · doi:10.1016/j.jad.2015.03.061 · Cited by 10

Relation Between V˙E/V˙CO2 Slope and Maximum Phonation Time in Chronic Heart Failure Patients

Izawa, K. P., Watanabe, S., Brubaker, P. H., Tochimoto, S., Hirano, Y., Matsushima, S., Suzuki, T., Oka, K., Saito, T., Omori, Y., et al. (2014) · Medicine · doi:10.1097/md.0000000000000306 · Cited by 10

Validation of the Spanish version of the McLean Screening Instrument for Borderline Personality Disorder

Soler, J., Domínguez‐Clavé, E., García‐Rizo, C., Vega, D., Elices, M., Martín‐Blanco, A., Feliu‐Soler, A., Carmona, C., & Pascual, J. C. (2016) · Revista de Psiquiatría y Salud Mental (English Edition) · doi:10.1016/j.rpsmen.2016.11.004 · Cited by 10

Wave Change of Intraoperative Transcranial Motor-Evoked Potentials During Corrective Fusion for Syndromic and Neuromuscular Scoliosis

Ando, K., Kobayashi, K., Ito, K., Tsushima, M., Morozumi, M., Tanaka, S. A., Machino, M., Ota, K., Nishida, Y., Ishiguro, N., et al. (2018) · Operative Neurosurgery · doi:10.1093/ons/opy045 · Cited by 10

Factors associated with falls in Japanese polio survivors

Imoto, D., Sawada, K., Horii, M., Hayashi, K., Yokota, M., Toda, F., Saitoh, E., Mikami, Y., & Kubo, T. (2019) · Disability and Rehabilitation · doi:10.1080/09638288.2018.1537381 · Cited by 10

Evaluation of bone metastasis burden as an imaging biomarker by quantitative single-photon emission computed tomography/computed tomography for assessing prostate cancer with bone metastasis: a phantom and clinical study

Motegi, K., Matsutomo, N., Yamamoto, T., & Koizumi, M. (2020) · Radiological Physics and Technology · doi:10.1007/s12194-020-00571-6 · Cited by 10

Development and Validation of ‘Prediction of Adverse Drug Reactions in Older Inpatients (PADROI)’ Risk Assessment Tool

Yadesa, T. M., Kitutu, F. E., Tamukong, R., & Alele, P. E. (2022) · Clinical Interventions in Aging · doi:10.2147/cia.s350500 · Cited by 10

Correlation of Pyuria and Bacteriuria in Acute Care

Cheng, B., Zaman, M., & Cox, W. M. (2022) · The American Journal of Medicine · doi:10.1016/j.amjmed.2022.04.022 · Cited by 10

Validating existing clinical cut-points for the parent-reported Strengths and Difficulties Questionnaire in a large sample of Canadian children and youth

Turner, S. E., Dopko, R. L., Goldfield, G. S., Cloutier, P., PAJER, K. A., Abdessemed, M., Mougharbel, F., Ranney, M., Hoffmann, M. D., & Lang, J. J. (2023) · Health Promotion and Chronic Disease Prevention in Canada · doi:10.24095/hpcdp.43.9.03 · Cited by 9

Association between cerebral oxygenation and usual parameters of cerebral perfusion in critically ill patients with acute brain injury

Ayasse, T., Gaugain, S., de Roquetaillade, C., Hermans-Didier, A., Kindermans, M., Chousterman, B. G., & Barthélémy, R. (2025) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1177/0271678x241310780 · Cited by 9

External validation and modification of nomogram for predicting positive resection margins before breast conserving surgery

Jung, J.-J., Kang, E., Kim, E., Kim, S. M., Jang, M., Yun, B. L., Park, S. Y., & Shin, H.-C. (2020) · Breast Cancer Research and Treatment · doi:10.1007/s10549-020-05779-z · Cited by 9

Validity of Clinical Symptoms Score to Discriminate Patients with COVID-19 from Common Cold Out-Patients in General Practitioner Clinics in Japan

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