Clinical Data Miner: An Electronic Case Report Form System With Integrated Data Preprocessing and Machine-Learning Libraries Supporting Clinical Diagnostic Model Research

Journals

1. Epstein E, Fischerova D, Valentin L, Testa A, Franchi D, Sladkevicius P, Frühauf F, Lindqvist P, Mascilini F, Fruscio R, Haak L, Opolskiene G, Pascual M, Alcazar J, Chiappa V, Guerriero S, Carlson J, Van Holsbeke C, Giuseppe Leone F, De Moor B, Bourne T, van Calster B, Installe A, Timmerman D, Verbakel J, Van den Bosch T. Ultrasound characteristics of endometrial cancer as defined by International Endometrial Tumor Analysis (IETA) consensus nomenclature: prospective multicenter study. Ultrasound in Obstetrics & Gynecology 2018;51(6):818 View
2. Eriksson L, Epstein E, Testa A, Fischerova D, Valentin L, Sladkevicius P, Franchi D, Frühauf F, Fruscio R, Haak L, Opolskiene G, Mascilini F, Alcazar J, Van Holsbeke C, Chiappa V, Bourne T, Lindqvist P, Van Calster B, Timmerman D, Verbakel J, Van den Bosch T, Wynants L. Ultrasound‐based risk model for preoperative prediction of lymph‐node metastases in women with endometrial cancer: model‐development study. Ultrasound in Obstetrics & Gynecology 2020;56(3):443 View
3. Rasmussen C, Van den Bosch T, Exacoustos C, Manegold‐Brauer G, Benacerraf B, Froyman W, Landolfo C, Condorelli M, Egekvist A, Josefsson H, Leone F, Jokubkiene L, Zannoni L, Epstein E, Installé A, Dueholm M. Intra‐ and Inter‐Rater Agreement Describing Myometrial Lesions Using Morphologic Uterus Sonographic Assessment: A Pilot Study. Journal of Ultrasound in Medicine 2019;38(10):2673 View
4. Yu C, Lin Y, Lin C, Lin S, Wu J, Chang S. Development of an Online Health Care Assessment for Preventive Medicine: A Machine Learning Approach. Journal of Medical Internet Research 2020;22(6):e18585 View
5. Sladkevicius P, Installé A, Van Den Bosch T, Timmerman D, Benacerraf B, Jokubkiene L, Di Legge A, Votino A, Zannoni L, De Moor B, De Cock B, Van Calster B, Valentin L. International Endometrial Tumor Analysis (IETA) terminology in women with postmenopausal bleeding and sonographic endometrial thickness ≥ 4.5 mm: agreement and reliability study. Ultrasound in Obstetrics & Gynecology 2018;51(2):259 View
6. Wei M, Wang Z, Wang X, Peng J, Song Y. Prediction of TBM penetration rate based on Monte Carlo-BP neural network. Neural Computing and Applications 2021;33(2):603 View
7. Van Schoubroeck D, Raine-Fenning N, Installé A, De Neubourg D, De Moor B, Bourne T, Van den Bosch T, Timmerman D. Interobserver agreement in assessment of polycystic ovarian morphology using pattern recognition. Ultrasound in Obstetrics & Gynecology 2016;47(5):652 View
8. Van Den Bosch T, Verbakel J, Valentin L, Wynants L, De Cock B, Pascual M, Leone F, Sladkevicius P, Alcazar J, Votino A, Fruscio R, Lanzani C, Van Holsbeke C, Rossi A, Jokubkiene L, Kudla M, Jakab A, Domali E, Epstein E, Van Pachterbeke C, Bourne T, Van Calster B, Timmerman D. Typical ultrasound features of various endometrial pathologies described using International Endometrial Tumor Analysis (IETA) terminology in women with abnormal uterine bleeding. Ultrasound in Obstetrics & Gynecology 2021;57(1):164 View
9. Galnares M, Nesmachnow S, Simini F. Instance-Based Learning Following Physician Reasoning for Assistance during Medical Consultation. Applied Sciences 2021;11(13):5886 View
10. Leonardi M, Uzuner C, Mestdagh W, Lu C, Guerriero S, Zajicek M, Dueckelmann A, Filippi F, Buonomo F, Pascual M, Stepniewska A, Ceccaroni M, Van den Bosch T, Timmerman D, Hudelist G, Condous G. Diagnostic accuracy of transvaginal ultrasound for detection of endometriosis using International Deep Endometriosis Analysis (IDEA) approach: prospective international pilot study. Ultrasound in Obstetrics & Gynecology 2022;60(3):404 View
11. Mitro N, Argyri K, Pavlopoulos L, Kosyvas D, Karagiannidis L, Kostovasili M, Misichroni F, Ouzounoglou E, Amditis A. AI-Enabled Smart Wristband Providing Real-Time Vital Signs and Stress Monitoring. Sensors 2023;23(5):2821 View
12. Eriksson L, Nastic D, Lindqvist P, Imboden S, Järnbert‐Pettersson H, Carlson J, Epstein E. Combination of Proactive Molecular Risk Classifier for Endometrial cancer (ProMisE) with sonographic and demographic characteristics in preoperative prediction of recurrence or progression of endometrial cancer. Ultrasound in Obstetrics & Gynecology 2021;58(3):457 View
13. Heremans R, Van den Bosch T, Valentin L, Wynants L, Pascual M, Fruscio R, Testa A, Buonomo F, Guerriero S, Epstein E, Bourne T, Timmerman D, Leone F. Ultrasound features of endometrial pathology in women without abnormal uterine bleeding: results from the International Endometrial Tumor Analysis study (IETA3). Ultrasound in Obstetrics & Gynecology 2022;60(2):243 View
14. Landolfo C, Ceusters J, Valentin L, Froyman W, Van Gorp T, Heremans R, Baert T, Wouters R, Vankerckhoven A, Van Rompuy A, Billen J, Moro F, Mascilini F, Neumann A, Van Holsbeke C, Chiappa V, Bourne T, Fischerova D, Testa A, Coosemans A, Timmerman D, Van Calster B. Comparison of the ADNEX and ROMA risk prediction models for the diagnosis of ovarian cancer: a multicentre external validation in patients who underwent surgery. British Journal of Cancer 2024;130(6):934 View
15. Heremans R, Wynants L, Valentin L, Leone F, Pascual M, Fruscio R, Testa A, Buonomo F, Guerriero S, Epstein E, Bourne T, Timmerman D, Van den Bosch T. Estimating risk of endometrial malignancy and other intracavitary uterine pathology in women without abnormal uterine bleeding using IETA‐1 multinomial regression model: validation study. Ultrasound in Obstetrics & Gynecology 2024;63(4):556 View