Artificial neural network models for the preoperative discrimination between malignant and benign adnexal masses
Abstract
Objective: The aim of this study was to generate and evaluate artificial neural network (ANN) models from simple clinical and ultrasound‐derived criteria to predict whether or not an adnexal mass will have histological evidence of malignancy. Design: The data were collected prospectively from 173 consecutive patients who were scheduled to undergo surgical investigations at the University Hospitals, Leuven, between August 1994 and August 1996. The outcome measure was the histological classification of excised tissues as malignant (including borderline) or benign. Methods: Age, menopausal status and serum CA 125 levels and sonographic features of the adnexal mass were encoded as variables. The ANNs were trained on a randomly selected set of 116 patient records and tested on the remainder ( n = 57). The performance of each model was evaluated using receiver operating characteristic (ROC) curves and compared with corresponding data from an established risk of malignancy index (RMI) and a logistic regression model. Results: There were 124 benign masses, five of borderline malignancy and 44 invasive cancers (of which 29% were metastatic); 37% of patients with a malignant or border‐line tumor had stage I disease. The best ANN gave an area under the ROC curve of 0.979 for the whole dataset, a sensitivity of 95.9% and specificity of 93.5%. The corresponding values for the RMI were 0.882, 67.3% and 91.1%, and for the logistic regression model 0.956, 95.9% and 85.5%, respectively. Conclusion: An ANN can be trained to provide clinically accurate information, on whether or not an adnexal mass is malignant, from the patient's menopausal status, serum CA 125 levels, and some simple ultrasonographic criteria. Copyright © 1999 International Society of Ultrasound in Obstetrics and Gynecology
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Several original studies published in this Journal have used AI methodology to evaluate adnexal masses, risk of lymph node metastases in endometrial cancer, pelvic organ function, breast lesions, aneuploidy risk, fetal lung maturity, perinatal outcome, shoulder dystocia, brain damage, gestational age in late pregnancy, and classify standard fetal brain images as normal or abnormal.
“Several original studies published in this Journal have used AI methodology to evaluate adnexal masses 21 , the risk of lymph node metastases in endometrial cancer 22 , pelvic organ function 23 , 24 and breast lesions 25 , 26 , 27 , assess aneuploidy risk 28 , predict fetal lung maturity 29 , perinatal outcome 30 , shoulder dystocia 31 and brain damage 32 , estimate gestational age in late pregnan”
From Introduction to artificial intelligence in ultrasound imaging in obstetrics and gynecology (2020) · cites this paper as [21]
Cites
Sassone, A. M., Timor‐Tritsch, I. E., Artner, A., Westhoff, C. L., & Warren, W. B. (1992) · Journal of diagnostic medical sonography · doi:10.1177/875647939200800127 · Cited by 547 · see citing works
Tingulstad, S., Hagen, B., Skjeldestad, F. E., Onsrud, M., Kiserud, T., Halvorsen, T. B., & Nustad, K. (1996) · BJOG An International Journal of Obstetrics & Gynaecology · doi:10.1111/j.1471-0528.1996.tb09882.x · Cited by 349 · see citing works
The influence of the operating surgeon's specialisation on patient survival in ovarian carcinoma
Kehoe, S. T., Powell, J., Wilson, S. E., & Woodman, C. B. J. (1994) · British Journal of Cancer · doi:10.1038/bjc.1994.440 · Cited by 163 · see citing works
Valentin, L., Sladkevicius, P., & Maršál, K. (1994) · PubMed · Cited by 144 · see citing works
Hata, K., Hata, T., Manabe, A., Sugimura, K., & Kitao, M. (1993) · International Journal of Gynecology & Obstetrics · doi:10.1016/0020-7292(93)90690-x · Cited by 84 · see citing works
Blood flow in benign ovarian tumors and normal ovaries during the follicular phase
Tekay, A., & Jouppila, P. I. (1995) · Obstetrics and Gynecology · doi:10.1016/0029-7844(95)00114-7 · Cited by 35 · see citing works
Levin, L., Lund, B., & Heintz, A. P. M. (1993) · Annals of Oncology · doi:10.1093/annonc/4.suppl_4.s23 · Cited by 29 · see citing works
Debulking and intervention surgery
Hacker, N. F., & van der Burg, M. E. L. (1993) · Annals of Oncology · doi:10.1093/annonc/4.suppl_4.s17 · Cited by 28 · see citing works
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Menon, U., Gentry‐Maharaj, A., Hallett, R., Ryan, A., Burnell, M., Sharma, A., Lewis, S., Davies, S., Philpott, S., Lopes, A. D. B., et al. (2009) · The Lancet Oncology · doi:10.1016/s1470-2045(09)70026-9 · Cited by 829 · see citing works
Timmerman, D., Testa, A. C., Bourne, T., Ferrazzi, E. M., Ameye, L., Konstantinovic, M. L., CALSTER, B. V., Collins, W. P., Vergote, I. B., Huffel, S. V., et al. (2005) · Journal of Clinical Oncology · doi:10.1200/jco.2005.01.7632 · Cited by 480 · see citing works
Self-citationMeys, E. M. J., Kaijser, J., Kruitwagen, R. F. P. M., Slangen, B. F. M., CALSTER, B. V., Aertgeerts, B., Verbakel, J. Y. J., Timmerman, D., & Gorp, T. V. (2016) · European Journal of Cancer · doi:10.1016/j.ejca.2016.01.007 · Cited by 273 · see citing works
Self-citationIntroduction to artificial intelligence in ultrasound imaging in obstetrics and gynecology
Drukker, L., Noble, J. A., & Papageorghiou, A. T. (2020) · Ultrasound in Obstetrics & Gynecology · doi:10.1002/uog.22122 · Cited by 240 · see citing works
Kaijser, J., Sayasneh, A., Hoorde, K. V., Ghaem‐Maghami, S., Bourne, T., Timmerman, D., & CALSTER, B. V. (2013) · Human Reproduction Update · doi:10.1093/humupd/dmt059 · Cited by 219 · see citing works
Self-citationKaijser, J., Bourne, T., Valentin, L., Sayasneh, A., Holsbeke, C. V., Vergote, I. B., Testa, A. C., Franchi, D., CALSTER, B. V., & Timmerman, D. (2012) · Ultrasound in Obstetrics and Gynecology · doi:10.1002/uog.12323 · Cited by 199 · see citing works
Self-citationThe Accuracy of Risk Scores in Predicting Ovarian Malignancy
Geomini, P. M. A. J., Kruitwagen, R. F. P. M., Bremer, G. L., Cnossen, J. S., & Mol, B. W. (2009) · Obstetrics and Gynecology · doi:10.1097/aog.0b013e318195ad17 · Cited by 185 · see citing works
Early Detection of Ovarian Cancer: Promise and Reality
Bast, R. C., Urban, N. D., Shridhar, V., Smith, D., Zhang, Z., Skates, S. J., Lu, K. H., Liu, J., Fishman, D. A., & Mills, G. B. (2002) · Cancer treatment and research · doi:10.1007/978-1-4757-3587-1_3 · Cited by 143 · see citing works
Exacoustós, C., Romanini, M. E., Amadio, A., Amoroso, C., Szabolcs, B., Zupi, E., & Arduini, D. (2007) · Journal of Clinical Ultrasound · doi:10.1002/jcu.20386 · Cited by 130 · see citing works
Distinguishing the Benign and Malignant Adnexal Mass: An External Validation of Prognostic Models
Mol, B. W., Boll, D., Kanter, M. D., Heintz, A. P. M., Sijmons, E. A., Oei, S. G., Bal, H., & Brölmann, H. A. M. (2001) · Gynecologic Oncology · doi:10.1006/gyno.2000.6052 · Cited by 109 · see citing works
Diagnostic accuracy of frozen section diagnosis of the adnexal mass: a metaanalysis
Geomini, P. M. A. J., Bremer, G. L., Kruitwagen, R. F. P. M., & Mol, B. W. (2004) · Gynecologic Oncology · doi:10.1016/j.ygyno.2004.09.042 · Cited by 105 · see citing works
Preoperative identification of a suspicious adnexal mass: A systematic review and meta-analysis
Dodge, J. E., Covens, A. L., Lacchetti, C., Elit, L. M., Le, T. V., Devries-Aboud, M., & Fung‐Kee‐Fung, M. (2012) · Gynecologic Oncology · doi:10.1016/j.ygyno.2012.03.048 · Cited by 103 · see citing works
Fernando Amor, L., Alcázar, J. L., Vaccaro, H., León, M., & Iturra, A. (2011) · Ultrasound in Obstetrics and Gynecology · doi:10.1002/uog.9012 · Cited by 100 · see citing works
The use of mathematical models to evaluate pelvic masses; can they beat an expert operator?
Timmerman, D. (2004) · Best Practice & Research Clinical Obstetrics & Gynaecology · doi:10.1016/j.bpobgyn.2003.09.009 · Cited by 95 · see citing works
Self-citationTimmerman, D., CALSTER, B. V., Jurkovic, D., Valentin, L., Testa, A. C., Bernard, J. P., Holsbeke, C. V., Huffel, S. V., Vergote, I. B., & Bourne, T. (2007) · Journal of Clinical Oncology · doi:10.1200/jco.2006.09.5943 · Cited by 96 · see citing works
Self-citationBenign ovarian cysts and ovarian cancer: a cohort study with implications for screening
Crayford, T. J. B., Campbell, S. C., Bourne, T., Rawson, H. J., & Collins, W. P. (2000) · The Lancet · doi:10.1016/s0140-6736(00)02038-9 · Cited by 93 · see citing works
Self-citationValue of Magnetic Resonance Imaging for the Diagnosis of Ovarian Tumors
Bazot, M., Daraï, É., Nassar-Slaba, J., Lafont, C., & Thomassin‐Naggara, I. (2008) · Journal of Computer Assisted Tomography · doi:10.1097/rct.0b013e31815881ef · Cited by 88 · see citing works
External Validation of Diagnostic Models to Estimate the Risk of Malignancy in Adnexal Masses
Van Holsbeke, C., Van Calster, B., Bourne, T., Ajossa, S., Testa, A. C., Guerriero, S., Fruscio, R., Lissoni, A. A., Czekierdowski, A., Savelli, L., et al. (2012) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-11-0879 · Cited by 87 · see citing works
Self-citationHolsbeke, C. V., CALSTER, B. V., Valentin, L., Testa, A. C., Ferrazzi, E. M., Dimou, I. N., Lü, C., Moerman, P., Huffel, S. V., Vergote, I. B., et al. (2007) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-06-2958 · Cited by 75 · see citing works
Self-citationPreoperative prediction of malignancy of ovarian tumors using least squares support vector machines
Lü, C., Gestel, T. V., Suykens, J. A. K., Huffel, S. V., Vergote, I. B., & Timmerman, D. (2003) · Artificial Intelligence in Medicine · doi:10.1016/s0933-3657(03)00051-4 · Cited by 75 · see citing works
Self-citationThe characterization of common ovarian cysts in premenopausal women
Jermy, K., Luise, C., & Bourne, T. (2001) · Ultrasound in Obstetrics and Gynecology · doi:10.1046/j.1469-0705.2001.00330.x · Cited by 74 · see citing works
Self-citationKnudsen, U. B., Tabor, A., Mosgaard, B. J., Andersen, E. S., Kjer, J. J., Hahn‐Pedersen, S., Toftager‐Larsen, K., & Mogensen, O. E. (2004) · Acta Obstetricia Et Gynecologica Scandinavica · doi:10.1080/j.0001-6349.2004.00607.x · Cited by 73 · see citing works
A decision support system to facilitate management of patients with acute gastrointestinal bleeding
Chu, A., Ahn, H., Halwan, B., Kalmin, B., Artifon, E. L. A., Barkun, A. N., Lagoudakis, M. G., & Kumar, A. (2007) · Artificial Intelligence in Medicine · doi:10.1016/j.artmed.2007.10.003 · Cited by 72 · see citing works
Prospective Evaluation of Logistic Regression Models for the Diagnosis of Ovarian Cancer
Aslam, N., BANERJEE, S., CARR, J. V., SAVVAS, M., HOOPER, R., & Jurkovic, D. (2000) · Obstetrics and Gynecology · doi:10.1016/s0029-7844(00)00835-8 · Cited by 71 · see citing works
Martínez-Más, J., Bueno-Crespo, A., Khazendar, S., Remezal-Solano, M., Martínez-Cendán, J.-P., Jassim, S., Du, H., Al Assam, H., Bourne, T., & Timmerman, D. (2019) · PLOS ONE · doi:10.1371/journal.pone.0219388 · Cited by 70 · see citing works
Self-citationYazbek, J., Raju, K. S., Ben‐Nagi, J., Holland, T., Hillaby, K., & Jurkovic, D. (2007) · Ultrasound in Obstetrics and Gynecology · doi:10.1002/uog.4002 · Cited by 70 · see citing works
Hillaby, K., Aslam, N., Salim, R., Lawrence, A., Raju, K. S., & Jurkovic, D. (2004) · Ultrasound in Obstetrics and Gynecology · doi:10.1002/uog.946 · Cited by 63 · see citing works
Abramowicz, J. S., & Timmerman, D. (2017) · American Journal of Obstetrics and Gynecology · doi:10.1016/j.ajog.2017.07.019 · Cited by 65 · see citing works
Self-citationArtificial intelligence (AI) in the detection of rectosigmoid deep endometriosis
Guerriero, S., Pascual, M. A., AJOSSA, S., Neri, M., Musa, E., Graupera, B., Rodríguez, I., & Alcázar, J. L. (2021) · European Journal of Obstetrics & Gynecology and Reproductive Biology · doi:10.1016/j.ejogrb.2021.04.012 · Cited by 62 · see citing works
Antal, P., Fannes, G., Timmerman, D., Moreau, Y., & Moor, B. D. (2003) · Artificial Intelligence in Medicine · doi:10.1016/s0933-3657(03)00053-8 · Cited by 57 · see citing works
Self-citationUltrasound and Assessment of Ovarian Cancer Risk
Twickler, D. M., & Moschos, E. (2010) · American Journal of Roentgenology · doi:10.2214/ajr.09.3562 · Cited by 55 · see citing works
Screening for ovarian cancer in the general population
Gentry‐Maharaj, A., & Menon, U. (2011) · Best Practice & Research Clinical Obstetrics & Gynaecology · doi:10.1016/j.bpobgyn.2011.11.006 · Cited by 54 · see citing works
Evaluation of Adnexal Masses With Three-Dimensional Ultrasonography
Geomini, P. M. A. J., Kluivers, K. B., Moret, E., Bremer, G. L., Kruitwagen, R. F. P. M., & Mol, B. W. (2006) · Obstetrics and Gynecology · doi:10.1097/01.aog.0000240138.24546.37 · Cited by 54 · see citing works
Prospective evaluation of three different models for the pre‐operative diagnosis of ovarian cancer
Aslam, N., Tailor, A., Lawton, F. E., Carr, J. V. L., Savvas, M., & Jurkovic, D. (2000) · BJOG An International Journal of Obstetrics & Gynaecology · doi:10.1111/j.1471-0528.2000.tb11646.x · Cited by 53 · see citing works
Trappen, P. O. V., Rufford, B., Mills, T. D., Sohaib, S. A., Webb, J. A. W., Sahdev, A., Carroll, M. J., Britton, K. E., Reznek, R. H., & Jacobs, I. J. (2006) · International Journal of Gynecological Cancer · doi:10.1111/j.1525-1438.2006.00753.x · Cited by 52 · see citing works
Tailor, A., Bourne, T., Campbell, S. C., Okokon, E. V., Dew, T. K., & Collins, W. P. (2003) · Ultrasound in Obstetrics and Gynecology · doi:10.1002/uog.65 · Cited by 50 · see citing works
Self-citationAramendía-Vidaurreta, V., Cabeza, R., Villanueva, A., Navallas, J., & Alcázar, J. L. (2016) · Ultrasound in Medicine & Biology · doi:10.1016/j.ultrasmedbio.2015.11.014 · Cited by 47 · see citing works
Ameye, L., Valentin, L., Testa, A. C., Holsbeke, C. V., Domali, E., Huffel, S. V., Vergote, I. B., Bourne, T., & Timmerman, D. (2008) · Ultrasound in Obstetrics and Gynecology · doi:10.1002/uog.6273 · Cited by 45 · see citing works
Self-citationPreoperative diagnosis of ovarian tumors using Bayesian kernel‐based methods
CALSTER, B. V., Timmerman, D., Lü, C., Suykens, J. A. K., Valentin, L., Holsbeke, C. V., Amant, F. C., Vergote, I. B., & Huffel, S. V. (2007) · Ultrasound in Obstetrics and Gynecology · doi:10.1002/uog.3996 · Cited by 42 · see citing works
Self-citationUnraveling a difficult diagnosis: the tricks for early recognition of ovarian cancer
Giampaolino, P., Corte, L. D., Foreste, V., Vitale, S. G., Chiofalo, B., Cianci, S., Zullo, F., & Bifulco, G. (2019) · Minerva Medica · doi:10.23736/s0026-4806.19.06086-5 · Cited by 41 · see citing works
Yazbek, J., Aslam, N., Tailor, A., Hillaby, K., Raju, K. S., & Jurkovic, D. (2006) · Ultrasound in Obstetrics and Gynecology · doi:10.1002/uog.2842 · Cited by 41 · see citing works
Borque‐Fernando, Á., Sanz, G., Allepuz, C., Plaza, L., GIL, P., & Rioja, L. A. (2001) · The Journal of Urology · doi:10.1016/s0022-5347(05)65651-0 · Cited by 39 · see citing works
Adnexal Masses Suspected to Be Benign Treated with Laparoscopy
Demir, R. H., & Marchand, G. J. (2012) · JSLS Journal of the Society of Laparoscopic & Robotic Surgeons · doi:10.4293/108680812x13291597716069 · Cited by 38 · see citing works
Applying Artificial Intelligence to Gynecologic Oncology: A Review
Mysona, D., Kapp, D. S., Rohatgi, A. P., Lee, D., Mann, A. K., Tran, P. M. H., Tran, L. K. H., She, J., & Chan, J. K. (2021) · Obstetrical & Gynecological Survey · doi:10.1097/ogx.0000000000000902 · Cited by 42 · see citing works
Lucidarme, O., Akakpo, J.-P., Granberg, S., Sideri, M. G., Levavi, H., Schneider, A., Autier, P., Nir, D., & Bleiberg, H. (2010) · European Radiology · doi:10.1007/s00330-010-1750-6 · Cited by 34 · see citing works
Assessment of a new logistic model in the preoperative evaluation of adnexal masses.
Alcázar, J. L., Errasti, T., Laparte, C., Jurado, M., & López-García, G. (2001) · Journal of Ultrasound in Medicine · doi:10.7863/jum.2001.20.8.841 · Cited by 32 · see citing works
Three‐dimensional ultrasonographic characteristics of endometriomata
Raine‐Fenning, N. J., Jayaprakasan, K., & Deb, S. (2008) · Ultrasound in Obstetrics and Gynecology · doi:10.1002/uog.5380 · Cited by 31 · see citing works
Lack of standardization in gynecological ultrasonography
Timmerman, D. (2000) · Ultrasound in Obstetrics and Gynecology · doi:10.1046/j.1469-0705.2000.00276.x · Cited by 29 · see citing works
Self-citationArtificial neural network computer prediction of ovarian malignancy in women with adnexal masses
Szpurek, D., Moszyński, R., Smoleń, A., & Sajdak, S. (2005) · International Journal of Gynecology & Obstetrics · doi:10.1016/j.ijgo.2005.01.034 · Cited by 28 · see citing works
Moszyński, R., Szpurek, D., Smoleń, A., & Sajdak, S. (2006) · International Journal of Gynecological Cancer · doi:10.1111/j.1525-1438.2006.00277.x · Cited by 27 · see citing works
Pediatric risk of malignancy index for preoperative evaluation of childhood ovarian tumors
Loh, A. H. P., Ong, C. L., Lam, S. L., Chua, J. H. Y., & Chui, C. H. (2011) · Pediatric Surgery International · doi:10.1007/s00383-011-3031-0 · Cited by 24 · see citing works
Stukan, M., Dudziak, M., Ratajczak, K., & Grabowski, J. P. (2015) · Journal of Ultrasound in Medicine · doi:10.7863/ultra.34.2.207 · Cited by 23 · see citing works
Koch, A. H., Jeelof, L. S., Muntinga, C. L. P., Gootzen, T. A., van de Kruis, N. M. A., Nederend, J., Boers, T. G. W., van der Sommen, F., & Piek, J. M. J. (2023) · Insights into Imaging · doi:10.1186/s13244-022-01345-x · Cited by 23 · see citing works
Sehgal, M. S. B., Gondal, I., & Dooley, L. S. (2005) · IEEE International Geoscience and Remote Sensing Symposium (IGARSS) · doi:10.1109/cibcb.2004.1393946 · Cited by 23 · see citing works
Bayesian networks in ovarian cancer diagnosis: potentials and limitations
Antal, P., Verrelst, H., Timmerman, D., Moreau, Y., Huffel, S. V., Moor, B. D., & Vergote, I. B. (2002) · Proceedings - IEEE Symposium on Computer-Based Medical Systems · doi:10.1109/cbms.2000.856886 · Cited by 24 · see citing works
Self-citationUsing artificial neural networks to predict malignancy of ovarian tumors
Lü, C., Brabanter, J. D., Huffel, S. V., Vergote, I. B., & Timmerman, D. (2005) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/iembs.2001.1020528 · Cited by 21 · see citing works
Self-citationRajimehr, R., Farsiu, S., Montaser‐Kouhsari, L., Bidari, A., Lucas, C. L., Yousefian, S., & Bahrami, F. (2002) · Lupus · doi:10.1191/0961203302lu226oa · Cited by 19 · see citing works
Seebacher, V., Aust, S., D’Andrea, D., Grimm, C., Reiser, E., Tiringer, D., von Mersi, H., Polterauer, S., Reinthaller, A., & Helmy-Bader, S. (2017) · PLoS ONE · doi:10.1371/journal.pone.0182383 · Cited by 21 · see citing works
Alcázar, J. L., & Jurado, M. (1999) · Journal of Ultrasound in Medicine · doi:10.7863/jum.1999.18.12.837 · Cited by 19 · see citing works
Boll, D. (2003) · BJOG An International Journal of Obstetrics & Gynaecology · doi:10.1016/s1470-0328(03)02961-6 · Cited by 19 · see citing works
Current developments in artificial intelligence from obstetrics and gynecology to urogynecology
Seval, M. M., & Varlı, B. (2023) · Frontiers in Medicine · doi:10.3389/fmed.2023.1098205 · Cited by 18 · see citing works
Giourga, M., Petropoulos, I., Stavros, S., Potiris, A., Gerede, A., Sapantzoglou, I., Fanaki, M., Papamattheou, E., Karasmani, C., Karampitsakos, T., et al. (2024) · Journal of Clinical Medicine · doi:10.3390/jcm13144123 · Cited by 17 · see citing works
Weichert, J., Welp, A., Scharf, J. L., Dracopoulos, C., Becker, W.-H., & Gembicki, M. (2021) · Geburtshilfe und Frauenheilkunde · doi:10.1055/a-1522-3029 · Cited by 17 · see citing works
K-Ranked Covariance Based Missing Values Estimation for Microarray Data Classification
Sehgal, M. S. B., Gondal, I., & Dooley, L. S. (2005) · International Conference on Hybrid Intelligent Systems (HIS) · doi:10.1109/ichis.2004.67 · Cited by 16 · see citing works
Timmerman, D., Verrelst, H., Collins, W. P., Bourne, T., & Vergote, I. B. (2001) · Gynecologic Oncology · doi:10.1006/gyno.2001.6317 · Cited by 15 · see citing works
Self-citationIntratumoral color Doppler analysis in endometrial carcinoma: is it clinically useful?
Testa, A. C., Ciampelli, M., Mastromarino, C., Lopez, R., Zannoni, G., Ferrandina, G., & Scambia, G. (2003) · Gynecologic Oncology · doi:10.1016/s0090-8258(02)00072-0 · Cited by 14 · see citing works
Importance of a specialized pathologist for the examination of frozen sections of adnexal masses
Fanfani, F., Zannoni, G. F., Fagotti, A., Gagliardi, M. L., Masciulloz, V., Testa, A. C., & Scambia, G. (2007) · International Journal of Gynecological Cancer · doi:10.1111/j.1525-1438.2007.00913.x · Cited by 14 · see citing works
García‐Mejido, J. A., Solis‐Martín, D., Martín‐Morán, M., de Paz, C. F.-C., Palacín, F. F., & Sainz‐Bueno, J. A. (2024) · International Urogynecology Journal · doi:10.1007/s00192-024-05841-0 · Cited by 13 · see citing works
Zhang, X., Meng, X., Dou, T., & Sun, H. (2020) · Experimental and Therapeutic Medicine · doi:10.3892/etm.2020.9395 · Cited by 13 · see citing works
Ledger, A., Ceusters, J., Valentin, L., Testa, A. C., Holsbeke, C. V., Franchi, D., Bourne, T., Froyman, W., Timmerman, D., & CALSTER, B. V. (2023) · BMC Medical Research Methodology · doi:10.1186/s12874-023-02103-3 · Cited by 12 · see citing works
Self-citationBorges, A. L., Brito, M., Ambrósio, P., Condeço, R., Pinto, P., Ambrósio, B., Mahomed, F., Gama, J. M. R., Bernardo, M. J., Gouveia, A., et al. (2024) · Ultrasound in Obstetrics and Gynecology · doi:10.1002/uog.27641 · Cited by 12 · see citing works
Khalaf, L. M. R., Desoky, H. H. M., Seifeldein, G. S., El-Sharkawy, M. A. M., Sayed, M. M., Ahmed, S. A., Rezk, K., & Hussien, M. T. (2019) · The Egyptian Journal of Radiology and Nuclear Medicine · doi:10.1186/s43055-019-0071-2 · Cited by 12 · see citing works
Probabilistic Graphical Models for Computational Biomedicine
Antal, P., Fannes, G., Moor, B. D., & Moreau, Y. (2003) · Methods of Information in Medicine · doi:10.1055/s-0038-1634328 · Cited by 12 · see citing works
CALSTER, B. V., Timmerman, D., Nabney, I. T., Valentin, L., Testa, A. C., Holsbeke, C. V., Vergote, I. B., & Huffel, S. V. (2007) · Neural Computing and Applications · doi:10.1007/s00521-007-0147-1 · Cited by 11 · see citing works
Self-citationUrban and rural differences in characteristics of ovarian cancer patients.
Szpurek, D., Moszyński, R., Szubert, S., & Sajdak, S. (2013) · PubMed · Cited by 11 · see citing works
Mathematical Models to Discriminate Between Benign and Malignant Adnexal Masses
Vaes, E., Manchanda, R., Nir, R., Nir, D., Bleiberg, H., Autier, P., Menon, U., & Robert, A. R. (2010) · International Journal of Gynecological Cancer · doi:10.1097/igc.0b013e3182000528 · Cited by 10 · see citing works
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Advanced statistical techniques: how to use your data more effectively?
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Self-citationAnnotated Bayesian networks: a tool to integrate textual and probabilistic medical knowledge
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Wang, R., Luo, H., & Cao, W. (2024) · Ultrasound in Obstetrics and Gynecology · doi:10.1002/uog.29116 · Cited by 7 · see citing works
Laparoscopic Supracervical Hysterectomy With Transcervical Morcellation: Our Experience
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Using logistic regression analysis in preliminary differential diagnosis of adnexal masses
Szpurek, D., Moszyński, R., AGATA, S., & Stefan, S. (2005) · International Journal of Gynecological Cancer · doi:10.1111/j.1525-1438.2005.00142.x · Cited by 7 · see citing works
Diagnostic performance of GI-RADS reporting system in evaluation of adnexal masses
elsalam, S. M. A., Hamed, S. T., & Sayed, M. A. E. (2020) · The Egyptian Journal of Radiology and Nuclear Medicine · doi:10.1186/s43055-020-00155-9 · Cited by 6 · see citing works
Rams, N., Muñoz, R., Moreno, C. S., & Parra, J. (2015) · Progresos de Obstetricia y Ginecología · doi:10.1016/j.pog.2014.11.020 · Cited by 6 · see citing works
Li, R., Lei, J., Tang, X., Zheng, S., Qu, J., Xu, Y., & Zheng, H. (2025) · Frontiers in Oncology · doi:10.3389/fonc.2025.1626286 · Cited by 4 · see citing works
Prömpeler, H. (2007) · Der Gynäkologe · doi:10.1007/s00129-007-2045-0 · Cited by 4 · see citing works
Classification of Ovarian Tumors Using Bayesian Least Squares Support Vector Machines
Lü, C., Gestel, T. V., Suykens, J. A. K., VanHuffel, S., Timmerman, D., & Vergote, I. B. (2003) · Lecture notes in computer science · doi:10.1007/978-3-540-39907-0_31 · Cited by 4 · see citing works
Self-citationLems, E., Koch, A. H., Delvaux, E. J. L. G., Leemans, J. C., Bongers, M. Y., Lok, C. A. R., Ramaekers, B. L. T., & Geomini, P. M. A. J. (2025) · Ultrasound in Obstetrics and Gynecology · doi:10.1002/uog.70135 · Cited by 3 · see citing works
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Sehgal, M. S. B., Gondal, I., & Dooley, L. S. (2004) · Open Research Online - ORO (The Open University) · Cited by 3 · see citing works
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Severi, F. M., Bocchi, C., Vannuccini, S., & Petraglia, F. (2012) · Florence Research (University of Florence) · Cited by 3 · see citing works
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Bihl, T., Young, W. A., & Weckman, G. R. (2018) · Advances in computer and electrical engineering book series · doi:10.4018/978-1-5225-7368-5.ch074 · Cited by 3 · see citing works
Antal, P., Fannes, G., Moor, B. D., Vandewalle, J. P. L., Moreau, Y., & Timmerman, D. (2001) · Lecture notes in computer science · doi:10.1007/3-540-48229-6_26 · Cited by 3 · see citing works
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Granberg, S., Ekerhovd, E., Timmerman, D., & Bourne, T. (2003) · Springer eBooks · doi:10.1007/978-1-4471-0655-5_21 · Cited by 3 · see citing works
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Aerts, S., Antal, P., Timmerman, D., Moor, B. D., & Moreau, Y. (2003) · Proceedings - IEEE Symposium on Computer-Based Medical Systems · doi:10.1109/cbms.2002.1011390 · Cited by 3 · see citing works
Self-citationJermy, K., & Bourne, T. (2003) · Elsevier eBooks · doi:10.1016/b978-012053642-9/50019-3 · Cited by 2 · see citing works
Self-citationThe parameters affecting accuracy of e ultrasonographic diagnosis in dermoid cysts
Tekın, Y. B., & Tekin, Y. B. (2014) · Dicle Medical Journal / Dicle Tip Dergisi · doi:10.5798/diclemedj.0921.2014.01.0374 · Cited by 2 · see citing works
Échographie des kystes et tumeurs de l'ovaire
Cotte, B., Haag, T. A., Vaudoyer, F., Canis, M. J., & Mage, G. (2011) · EMC - Gynécologie · doi:10.1016/s0246-1064(11)50383-4 · Cited by 2 · see citing works
- Authors
- Timmerman, D., Verrelst, H., Bourne, T. H., De Moor, B., Collins, W. P., Vergote, I., & Vandewalle, J.
- Affiliations
- Universitair Ziekenhuis Leuven (BE)
- KU Leuven (BE)
- St George's Hospital (GB)
- King's College London (GB)
- Corresponding author
- Timmerman, D.
- Venue
- Ultrasound in Obstetrics & Gynecology
- Publisher
- Wiley
- Published
- 1999-01
- Volume
- 13
- Issue
- 1
- Pages
- 17-25
- ISSN
- 0960-7692 (ISSN-L)
- 1469-0705
- OpenAlex
- W2081425519
- Cited by
- 134
- References
- 8
- Citations by year
- 2026: 3 · 2025: 2 · 2024: 6 · 2023: 5 · 2022: 6 · 2021: 4 · 2020: 3 · 2019: 4 · 2018: 2 · 2017: 4 · 2016: 1 · 2015: 5 · 2014: 3 · 2013: 2 · 2012: 4
- FWCI
- 6.18
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Ultrasound in Obstetrics and Gynecology (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Reproductive Medicine › Ovarian cancer diagnosis and treatment
- Physical Sciences › Computer Science › Artificial Intelligence › AI in cancer detection
- Health Sciences › Health Professions › Health Information Management › Artificial Intelligence in Healthcare
- Keywords
- adnexal mass, ovarian cancer, artificial neural networks, CA125, risk of malignancy index, sonographic features, menopausal status, borderline ovarian tumors, diagnostic accuracy
- MeSH terms
- Adnexal Diseases, Adult, Aged, Aged, 80 and over, Computer Simulation, Female, Humans, Middle Aged, Neoplasm Staging, Ovarian Neoplasms, Predictive Value of Tests, Preoperative Care, Prospective Studies, Random Allocation, ROC Curve, Vagina, Reproducibility of Results, Discriminant Analysis, Neural Networks, Computer, CA-125 Antigen, Ultrasonography, Doppler, Color, Endosonography
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