GenoML: Automated Machine Learning for Genomics

Autor: Makarious, Mary B., Leonard, Hampton L., Vitale, Dan, Iwaki, Hirotaka, Saffo, David, Sargent, Lana, Dadu, Anant, Castaño, Eduardo Salmerón, Carter, John F., Maleknia, Melina, Botia, Juan A., Blauwendraat, Cornelis, Campbell, Roy H., Hashemi, Sayed Hadi, Singleton, Andrew B., Nalls, Mike A., Faghri, Faraz

GenoML is a Python package automating machine learning workflows for genomics (genetics and multi-omics) with an open science philosophy. Genomics data require significant domain expertise to clean, pre-process, harmonize and perform quality control

Externí odkaz: http://arxiv.org/abs/2103.03221

Identifying and predicting amyotrophic lateral sclerosis clinical subgroups: a population-based machine-learning study

Autor: Chiò, Adriano, Calvo, Andrea, Moglia, Cristina, Canosa, Antonio, Manera, Umberto, Vasta, Rosario, Palumbo, Francesca, Bombaci, Alessandro, Grassano, Maurizio, Brunetti, Maura, Casale, Federico, Fuda, Giuseppe, Salamone, Paolina, Iazzolino, Barbara, Peotta, Laura, Cugnasco, Paolo, De Marco, Giovanni, Torrieri, Maria Claudia, Gallone, Salvatore, Barberis, Marco, Sbaiz, Luca, Gentile, Salvatore, Mauro, Alessandro, Mazzini, Letizia, De Marchi, Fabiola, Corrado, Lucia, D'Alfonso, Sandra, Bertolotto, Antonio, Imperiale, Daniele, De Mattei, Marco, Amarù, Salvatore, Comi, Cristoforo, Labate, Carmelo, Poglio, Fabio, Ruiz, Luigi, Testa, Lucia, Rota, Eugenia, Ghiglione, Paolo, Launaro, Nicola, Di Sapio, Alessia, Mandrioli, Jessica, Fini, Nicola, Martinelli, Ilaria, Zucchi, Elisabetta, Gianferrari, Giulia, Simonini, Cecilia, Meletti, Stefano, Liguori, Rocco, Vacchiano, Veria, Salvi, Fabrizio, Bartolomei, Ilaria, Michelucci, Roberto, Cortelli, Pietro, Rinaldi, Rita, Borghi, Anna Maria, Zini, Andrea, Sette, Elisabetta, Tugnoli, Valeria, Pugliatti, Maura, Canali, Elena, Codeluppi, Luca, Valzania, Franco, Zinno, Lucia, Pavesi, Giovanni, Medici, Doriana, Pilurzi, Giovanna, Terlizzi, Emilio, Guidetti, Donata, De Pasqua, Silvia, Santangelo, Mario, De Massis, Patrizia, Bracaglia, Martina, Casmiro, Mario, Querzani, Pietro, Morresi, Simonetta, Longoni, Marco, Patuelli, Alberto, Malagù, Susanna, Currò Dossi, Marco, Vidale, Simone, Ferro, Salvatore, Faghri, Faraz, Brunn, Fabian, Dadu, Anant, Nalls, Michael A, Campbell, Roy H, Traynor, Bryan J ^*

Publikováno v: In The Lancet Digital Health May 2022 4(5):e359-e369

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dAFM: Fusing Psychometric and Connectionist Modeling for Q-matrix Refinement

Autor: Pardos, Zachary A., Dadu, Anant

We introduce a model which combines principles from psychometric and connectionist paradigms to allow direct Q-matrix refinement via backpropagation. We call this model dAFM, based on augmentation of the original Additive Factors Model (AFM), whose c

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0201231cf9d6e109686c8fe0bb90a03e