Development and International Evaluation of an Artificial Intelligence-based Model (PROGRxN-BCa) Using the World Health Organization 2004/2022 Grading System to Predict Progression Risk and Improve Substratification for Non-muscle-invasive Bladder Cancer.
AuteursKwong JCC, Al-Daqqaq Z, Chelliahpillai Y, Lee S, Kim K, Ringa M, Feifer A, Lajkosz K, Wettstein MS, Chan A, Lee T, Nguyen M, Kassouf W, Black PC, Breau RH, Lodde M, Fairey A, Lattouf JB, Jeldres C, Rendon R, Alimohamed N, Fleshner NE, Diamand R, Gontero P, Sylvester RJ, van Rhijn BWG, Kamat AM, Johnson AEW, Zlotta AR, Kulkarni GS
Leveraging Sarcopenia index by automated CT body composition analysis for pan cancer prognostic stratification.
AuteursBorys K, Haubold J, Keyl J, Bali MA, De Angelis R, Boni KB, Coquelet N, Kohnke J, Baldini G, Kroll L, Schramm S, Stang A, Malamutmann E, Kleesiek J, Kim M, Kasper S, Siveke JT, Wiesweg M, Merkel-Jens A, Schaarschmidt BM, Gruenwald V, Bauer S, Oezcelik A, Bölükbas S, Herrmann K, Kimmig R, Lang S, Treckmann J, Stuschke M, Hadaschik B, Umutlu L, Forsting M, Schadendorf D, Friedrich CM, Schuler M, Hosch R, Nensa F
Immunophenotypic changes in the tumor and tumor microenvironment during progression to multiple myeloma.
AuteursBergiers I, Köse MC, Skerget S, Malfait M, Fourneau N, Ellis JC, Vanhoof G, Smets T, Verbist B, De Maeyer D, Van Houdt J, Van der Borght K, Verona R, Heidrich B, Kurth W, Delforge M, Meuleman N, Van Droogenbroeck J, Vlummens P, Heuck CJ, Beguin Y, Bahlis N, Casneuf T, Caers J
RSC4All as a machine learning nomogram to predict RSClin™ results in HR+/HER2- node-negative early breast cancer.
AuteursJacobs F, D'Amico S, Ferraro E, Agostinetto E, Tondini C, Gaudio M, Benvenuti C, Gerosa R, Saltalamacchia G, Zazzetti E, Di Rienzo R, Buonaiuto R, Martorana F, Chirco A, De Sanctis R, Della Porta MG, Santoro A, Vigneri P, Arpino MG, Giuliano M, Fornier M, de Azambuja E, Zambelli A
35 years of academic trials focusing on high-dose therapy and autologous stem cell transplantation: the Intergroupe Francophone du Myélome (IFM) experience.
AuteursMoreau P, Hulin C, Talbot A, Demarquette H, Caillot L, Chalopin T, Bobin A, Manier S, Leleu X, Karlin L, Caillot D, Sonntag C, Feugier P, Roussel M, Gounot R, Macro M, Mohty M, Garderet L, Tiab M, Orsini-Piocelle F, Vincent L, Meuleman N, Fontan J, Montes L, Vekemans MC, Escoffre-Barbe M, Eveillard JR, Schiano de Colella JM, Lambert J, Mary JY, Fermand JP, Arnulf B, Corre J, Avet-Loiseau H, Facon T, Harousseau JL, Touzeau C, Perrot A
