| Discovery of frequent datalog patterns L Dehaspe, H Toivonen Data Mining and knowledge discovery 3 (1), 7-36, 1999 | 478 | 1999 |
| Finding Frequent Substructures in Chemical Compounds. L Dehaspe, H Toivonen, RD King KDD 98, 1998, 1998 | 407 | 1998 |
| Clausal discovery L De Raedt, L Dehaspe Machine Learning 26 (2), 99-146, 1997 | 387 | 1997 |
| Mining association rules in multiple relations L Dehaspe, LD Raedt International Conference on Inductive Logic Programming, 125-132, 1997 | 327 | 1997 |
| Discovery of relational association rules L Dehaspe, H Toivonen Relational data mining, 189-212, 2001 | 187 | 2001 |
| Presymptomatic identification of cancers in pregnant women during noninvasive prenatal testing F Amant, M Verheecke, I Wlodarska, L Dehaspe, P Brady, N Brison, ... JAMA oncology 1 (6), 814-819, 2015 | 184 | 2015 |
| Improving the efficiency of inductive logic programming through the use of query packs H Blockeel, L Dehaspe, B Demoen, G Janssens, J Ramon, ... Journal of Artificial Intelligence Research 16, 135-166, 2002 | 165 | 2002 |
| A four‐gene methylation marker panel as triage test in high‐risk human papillomavirus positive patients JJH Eijsink, A Lendvai, V Deregowski, HG Klip, G Verpooten, L Dehaspe, ... International Journal of Cancer 130 (8), 1861-1869, 2012 | 162 | 2012 |
| Warmr: a data mining tool for chemical data RD King, A Srinivasan, L Dehaspe Journal of Computer-Aided Molecular Design 15 (2), 173-181, 2001 | 118 | 2001 |
| Non-invasive detection of genomic imbalances in Hodgkin/Reed-Sternberg cells in early and advanced stage Hodgkin's lymphoma by sequencing of circulating cell-free DNA: a … P Vandenberghe, I Wlodarska, T Tousseyn, L Dehaspe, D Dierickx, ... The Lancet Haematology 2 (2), e55-e65, 2015 | 113 | 2015 |
| Noninvasive prenatal testing using a novel analysis pipeline to screen for all autosomal fetal aneuploidies improves pregnancy management B Bayindir, L Dehaspe, N Brison, P Brady, S Ardui, M Kammoun, ... European Journal of Human Genetics 23 (10), 1286-1293, 2015 | 110 | 2015 |
| The utility of different representations of protein sequence for predicting functional class RD King, A Karwath, A Clare, L Dehaspe Bioinformatics 17 (5), 445-454, 2001 | 108 | 2001 |
| Accurate prediction of protein functional class from sequence in the Mycobacterium tuberculosis and Escherichia coli genomes using data mining RD King, A Karwath, A Clare, L Dehaspe Yeast 17 (4), 283-293, 2000 | 90 | 2000 |
| Frequent pattern discovery in first-order logic L Dehaspe | 77 | 1998 |
| Executing query packs in ILP H Blockeel, L Dehaspe, B Demoen, G Janssens, J Ramon, ... International Conference on Inductive Logic Programming, 60-77, 2000 | 68 | 2000 |
| Three companions for data mining in first order logic LD Raedt, H Blockeel, L Dehaspe, WV Laer Relational data mining, 105-139, 2001 | 64 | 2001 |
| Maximum entropy modeling with clausal constraints L Dehaspe International Conference on Inductive Logic Programming, 109-124, 1997 | 64 | 1997 |
| Predicting fetoplacental chromosomal mosaicism during non‐invasive prenatal testing N Brison, M Neofytou, L Dehaspe, B Bayindir, K Van Den Bogaert, ... Prenatal diagnosis 38 (4), 258-266, 2018 | 63 | 2018 |
| Genome scale prediction of protein functional class from sequence using data mining RD King, A Karwath, A Clare, L Dephaspe Proceedings of the sixth ACM SIGKDD international conference on Knowledge …, 2000 | 57 | 2000 |
| Parallel inductive logic programming L Dehaspe, L De Raedt The MLnet Familiarization Workshop on Statistics, Machine Learning and …, 1995 | 55 | 1995 |
