International consortium for integrative genomics prediction

Livrables

Plan of data standards for genetic risk scores
Report of available data resources and plan for data harmonization strategy
Access to a biobank data set through implementation of local biobank APIs and cloud resources to support federated consortium access
Implementation of phenotype harmonization
Access to first INTERVENE consortium data sets available from EMBL-EBI and CSC Cloud services

Access to first INTERVENE consortium data sets available from EMBLEBI and CSC Cloud services

Genetic validation of disease endpoints
Review of the consortium partner biobank and data collections, including access policies

Review of the consortium partner biobank and data collections including access policies

Data coordination centre established
INTERVENE consortium AI algorithms supported by CSC HPC environment on synthetic data.

INTERVENE consortium AI algorithms supported by CSC HPC environment on synthetic data

Disease endpoint selection based on available resources and AI based methods

Publications

Systematic comparison of family history and polygenic risk across 24 common diseases

Auteurs: Nina Mars, Joni V. Lindbohm, Pietro della Briotta Parolo, Elisabeth Widén, Jaakko Kaprio, Aarno Palotie, FinnGen, Samuli Ripatti
Publié dans: AJHG, Numéro Vol 109, Numéro 12, 2022, Page(s) 2152-2162, ISSN 0002-9297
Éditeur: University of Chicago Press
DOI: 10.1016/j.ajhg.2022.10.009

A cross-disorder dosage sensitivity map of the human genome

Auteurs: The members of the Estonian Biobank Research Team are Andres Metspalu, Reedik Mägi, Mari Nelis, Lili Milani, and Tõnu Esko. Ryan L. Collins, Joseph T. Glessner, Eleonora Porcu, ..., Shamil Sunyaev, Harrison Brand, Michael E. Ta
Publié dans: Cell, Numéro 185, 2022, Page(s) 3041-3055, ISSN 1097-4172
Éditeur: Cell Press
DOI: 10.1016/j.cell.2022.06.036

Genetic predictors of lifelong medication-use patterns in cardiometabolic diseases

Auteurs: Kiiskinen T, Helkkula P, Krebs K, Karjalainen J, Saarentaus E, Mars N, Lehisto A, Zhou W, Cordioli M, Jukarainen S, Rämö JT, Mehtonen J, Veerapen K, Räsänen M, Ruotsalainen S, Maasha M; FinnGen; Niiranen T, Tuomi T, Salomaa V, Kurki M, Pirinen M, Palotie A, Daly M, Ganna A, Havulinna AS, Milani L, Ripatti S.
Publié dans: Nature Medicine, Numéro 29, 2023, Page(s) 209-218, ISSN 1546-170X
Éditeur: Nature
DOI: 10.1038/s41591-022-02122-5

Gene-Gene Interaction Detection with Deep Learning

Auteurs: Tianyu Cui, Khaoula El Mekkaoui, Jaakko Reinvall, Aki S. Havulinna, Pekka Marttinen, Samuel Kaski
Publié dans: Communications Biology, Numéro Vol 5, article 1238, 2022, ISSN 0028-0836
Éditeur: Nature Publishing Group
DOI: 10.1101/2021.03.12.435063

Carriers of ADAMTS13 Rare Variants Are at High Risk of Life-Threatening COVID-19

Auteurs: Kristina Zguro,Margherita Baldassarri,Francesca Fava,Giada Beligni,Sergio Daga,Roberto Leoncini,Lucrezia Galasso,Michele Cirianni,Stefano Rusconi,...Giuseppe Marotta,Simone Furini,GEN-COVID Multicenter Study,Alessandra Renieri, Chiara Fallerini
Publié dans: Viruses, Numéro 14(6), 2022, ISSN 1999-4915
Éditeur: Multidisciplinary Digital Publishing Institute (MDPI)
DOI: 10.3390/v14061185

Inframe insertion and splice site variants in MFGE8 associate with protection against coronary atherosclerosis

Auteurs: Sanni E. Ruotsalainen, Ida Surakka, Nina Mars, Juha Karjalainen, Mitja Kurki, Masahiro Kanai, Kristi Krebs, Sarah Graham, Pashupati P. Mishra, Binisha H. Mishra, Juha Sinisalo, Priit Palta, Terho Lehtimäki, Olli Raitakari, Estonian Biobank Research Team, Lili Milani, The Biobank Japan Project, Yukinori Okada, FinnGen, Aarno Palotie, Elisabeth Widen, Mark J. Daly & Samuli Ripatt
Publié dans: Nature, Numéro 5, 2022, Page(s) article 802, ISSN 0028-0836
Éditeur: Nature Publishing Group
DOI: 10.1038/s42003-022-03552-0

An explainable model of host genetic interactions linked to COVID-19 severity

Auteurs: Anthony Onoja, Nicola Picchiotti, Chiara Fallerini, Margherita Baldassarri, Francesca Fava, GEN-COVID Multicenter Study, Francesca Colombo, Francesca Chiaromonte, Alessandra Renieri, Simone Furini & Francesco Raimondi
Publié dans: Nature, Comm. Biology, Numéro Vol 5, 2022, Page(s) Article 1133, ISSN 2399-3642
Éditeur: Nature
DOI: 10.1038/s42003-022-04073-6

Global Biobank analyses provide lessons for developing polygenic risk scores across diverse cohorts

Auteurs: Ying Wang, Shinichi Namba, Esteban Lopera, Sini Kerminen Kristin Tsuo, Kristi Läll, Masahiro Kanai, Wei Zhou, Kuan-Han Wu, Marie-Julie Favé, Laxmi Bhatta, Philip Awadalla, Ben Brumpton, Patrick Deelen, Kristian Hveem, Valeria Lo Faro, Reedik Mägi, Yoshinori Murakami, Serena Sanna, Jordan W. Smoller…Jibril Hirbo
Publié dans: Cell Genomics, Numéro Vol 3, Numéro 1, 2023, ISSN 2666-979X
Éditeur: Cell Press
DOI: 10.1101/2021.11.18.21266545

Responsible use of polygenic risk scores in the clinic: potential benefits, risks and gaps

Auteurs: Adebowale Adeyemo, Mary K. Balaconis, Deanna R. Darnes, Segun Fatumo, Palmira Granados Moreno, Chani J. Hodonsky, Michael Inouye, Masahiro Kanai, Kazuto Kato, Bartha M. Knoppers, Anna C. F. Lewis, Alicia R. Martin, Mark I. McCarthy, Michelle N. Meyer, Yukinori Okada, J. Brent Richards, Lucas Richter, Samuli Ripatti, Charles N. Rotimi, Saskia C. Sanderson, Amy C. Sturm, Ricardo A. Verdugo, Elisabet
Publié dans: Nature Medicine, Numéro 27, 2021, Page(s) 1876-1884, ISSN 1078-8956
Éditeur: Nature Publishing Group
DOI: 10.1038/s41591-021-01549-6

Multitask Balanced and Recalibrated Network for Medical Code Prediction

Auteurs: Wei Sun, Shaoxiong Ji, Erik Cambria, Pekka Marttinen
Publié dans: ACM Transactions on Intelligent Systems and Technology, Numéro Vol 14, Numéro 1, 2022, Page(s) 1-20, ISSN 2157-6904
Éditeur: Association for Computing Machinery (ACM)
DOI: 10.1145/3563041

Ethical layering in AI-driven polygenic risk scores—New complexities, new challenges

Auteurs: Fritzsche, M.-C., Akyüz, K., Cano Abadía, M., McLennan, S., Marttinen, P., Mayrhofer, M. T., & Buyx, A. M. (2023). Ethical layering in AI-driven polygenic risk scores—Fritzsche, M.-C., Akyüz, K., Cano Abadía, M., McLennan, S., Marttinen, P., Mayrhofer, M. T., & Buyx, A. M
Publié dans: Frontiers in Genetics, Numéro 14, 2023, ISSN 1664-8021
Éditeur: Frontiers Media
DOI: 10.3389/fgene.2023.1098439

Polygenic scores in biomedical research

Auteurs: Iftikhar J. Kullo, Cathryn M. Lewis, Michael Inouye, Alicia R. Martin, Samuli Ripatti & Nilanjan Chatterjee
Publié dans: Nature Reviews Genetics, Numéro 23, 2022, Page(s) 524-532, ISSN 1471-0056
Éditeur: Nature Publishing Group
DOI: 10.1038/s41576-022-00470-z

Multiparametric Platform for Profiling Lipid Trafficking in Human Leukocytes: Application for Hypercholesterolemia

Auteurs: Simon G. Pfisterer; Ivonne Brock; Ivonne Brock; Kristiina Kanerva; Kristiina Kanerva; Iryna Hlushchenko; Lassi Paavolainen; Pietari Ripatti; Mohammad Majharul Islam; Aija Kyttala; Maria Donata Di Taranto; Annalisa Scotto di Frega; Giuliana Fortunato; Johanna Kuusisto; Peter Horvath; Samuli Ripatti; Samuli Ripatti; Markku Laakso; Elina Ikonen; Elina Ikonen
Publié dans: Cell Reports Methods, Numéro Vol 2,issue 2, 2022, ISSN 0346-251X
Éditeur: Pergamon Press Ltd.
DOI: 10.1101/2021.04.19.440471

Genetic risk factors have a substantial impact on healthy life years

Auteurs: Aki Havulinna; Sakari Jukarainen; Nina Mars
Publié dans: Nature Medicine, Numéro 27, 2021, Page(s) 1876-1884, ISSN 1078-8956
Éditeur: Nature Publishing Group
DOI: 10.1101/2022.01.25.22269831v1

Ultra-rare RTEL1 gene variants associate with acute severity of COVID-19 and evolution to pulmonary fibrosis as a specific long COVID disorder

Auteurs: Laura Bergantini, Margherita Baldassarri, Miriana d’Alessandro, Giulia Brunelli, Gaia Fabbri, Kristina Zguro, Andrea Degl’Innocenti, GEN-COVID Multicenter study, Chiara Fallerini, Elena Bargagli & Alessandra Renieri
Publié dans: Respiratory Research, Numéro 24, 2023, Page(s) article no 158, ISSN 1465-9921
Éditeur: BioMed Central
DOI: 10.1186/s12931-023-02458-7

Pathogen-sugar interactions revealed by universal saturation transfer analysis

Auteurs: Charles J. Buchanan, Ben Gaunt, Peter J. Harrison, Yun Yang, Jiwei Liu, Aziz Khan, Andrew M. Giltrap, Audrey Le Bas, Philip N. Ward, Kapil Gupta, Maud Dumoux, Tiong Kit Tan, Lisa Schimaski, Sergio Daga, Nicola Picchiotti, Margherita Baldassarri, Elisa Benetti, Chiara Fallerini, Francesca Fava, Annarita Giliberti, Panagiotis I. Koukos, Matthew J. Davy, Abirami Lakshminarayanan, Xiaochao Xue, Georgi
Publié dans: Science, Numéro 377, 2022, ISSN 0065-7085
Éditeur: American Association for the Advancement of Science
DOI: 10.1126/science.abm3125

Informative Bayesian Neural Network Priors for Weak Signals

Auteurs: Tianyu Cui, Aki Havulinna, Pekka Marttinen, Samuel Kaski
Publié dans: Bayesian Anal., 2021, Page(s) 1-31 (2021), ISSN 1936-0975
Éditeur: Carnegie Mellon University
DOI: 10.1214/21-ba1291

Machine learning optimized polygenic scores for blood cell traits identify sex-specific trajectories and genetic correlations with disease.

Auteurs: Yu Xu, Dragana Vuckovic, Scott C. Ritchie, ..., John Danesh, Nicole Soranzo, Michael Inouye
Publié dans: Cell Genomics, Numéro Vol 2, Numéro 1, 2022, ISSN 2666-979X
Éditeur: Cell Press
DOI: 10.1016/j.xgen.2021.100086

Omics-informed CNV calls reduce false-positive rates and improve power for CNV-trait associations

Auteurs: Maarja Lepamets; Chiara Auwerx; Margit Nõukas; Annique Claringbould; Eleonora Porcu; Mart Kals; Tuuli Jürgenson; Andrew Paul Morris; Urmo Võsa; Murielle Bochud; Silvia Stringhini; Cisca Wijmenga; Lude Franke; Hedi Peterson; Jaak Vilo; Kaido Lepik; Reedik Mägi; Zoltán Kutalik
Publié dans: HGG advances,, Numéro vol. 3, no. 4, 2022, Page(s) pp. 100133, ISSN 0346-251X
Éditeur: Pergamon Press Ltd.
DOI: 10.1016/j.xhgg.2022.100133

Ethical layering in AI-driven polygenic risk scores – new complexities, new challenges

Auteurs: Fritzsche, M., Akyüz, K., Abadía, M.C., McLennan, S., Marttinen, P. Mayrhofer, M.T., and Buyx, A.M.
Publié dans: Frontiers in Genetics, Numéro Vol 4, 2023, ISSN 1664-8021
Éditeur: Frontiers Media
DOI: 10.3389/fgene.2023.1098439

Genome-wide association studies of metabolites in Finnish men identify disease-relevant loci

Auteurs: Nina Mars, Sini Kerminen, Yen-Chen A. Feng, Masahiro Kanai, Kristi Läll, Laurent F. Thomas, Anne Heidi Skogholt, Pietro della Briotta Parolo, The Biobank Japan Project, FinnGen, Benjamin M. Neale, Jordan W. Smoller, Maiken E. Gabrielsen, Kristian Hveem, Reedik Mägi, Koichi Matsuda, Yukinori Okada, Matti Pirinen, Aarno Palotie, Andrea Ganna, Alicia R. Martin
Publié dans: Cell Genomics, Numéro 2, Numéro 4, 2022, ISSN 2666-979X
Éditeur: CellPress
DOI: 10.1038/s41467-022-29143-5

Genome-wide risk prediction of common diseases across ancestries in one million people.

Auteurs: Nina Mars, Sini Kerminen, Yen-Chen A. Feng, Masahiro Kanai, Kristi Läll, Laurent F. Thomas, Anne Heidi Skogholt, Pietro della Briotta Parolo, The Biobank Japan Project, FinnGen, Benjamin M. Neale, Jordan W. Smoller, Maiken E. Gabrielsen, Kristian Hveem, Reedik Mägi, Koichi Matsuda, Yukinori Okada, Matti Pirinen, Aarno Palotie, Andrea Ganna, Alicia R. Martin
Publié dans: Cell Genomics, Numéro Apr 13; 2(4), 2023, ISSN 2666-979X
Éditeur: Cell Press
DOI: 10.1016/j.xgen.2022.100118

Identifying interpretable gene-biomarker associations with functionally informed kernel-based tests in 190,000 exomes

Auteurs: Remo Monti, Pia Rautenstrauch, Mahsa Ghanbari, Alva Rani James, Uwe Ohler, Stefan Konigorski, Christoph Lippert
Publié dans: Nature Communications, Numéro Vol 13, article 5332, 2022, Page(s) 1-16, ISSN 2041-1723
Éditeur: Nature Publishing Group
DOI: 10.1101/2021.05.27.444972

Host genetic basis of COVID-19: from methodologies to genes

Auteurs: Kristina Zguro, Chiara Fallerini, Francesca Fava, Simone Furini & Alessandra Renieri
Publié dans: EJHG, Numéro Vol 30, 2022, Page(s) 899-907, ISSN 1018-4813
Éditeur: Natue Publishing Group
DOI: 10.1038/s41431-022-01121-x

Knowledge-augmented Graph Neural Networks with Concept-aware Attention for Adverse Drug Event Detection

Auteurs: Ji, Shaoxiong; Gao, Ya; Marttinen, Pekka
Publié dans: Arxiv, Numéro 6, 2023, ISSN 2331-8422
Éditeur: Cornell University
DOI: 10.48550/arxiv.2301.10451

Challenges and Opportunities for Developing More Generalizable Polygenic Risk Scores

Auteurs: Ying Wang, Kristin Tsuo, Masahiro Kanai, Benjamin M. Neale, Alicia R. Martin
Publié dans: Annual Rev of Biomed. Data Science, Numéro Vol 5, 2022, Page(s) 293-320, ISSN 2574-3414
Éditeur: Annual Reviews
DOI: 10.1146/annurev-biodatasci-111721-074830

Advancing our understanding of genetic risk factors and potential personalized strategies for pelvic organ prolapse

Auteurs: Natàlia Pujol-Gualdo, Kristi Läll, Maarja Lepamets, Estonian Biobank Research Team, Henna-Riikka Rossi, Riikka K. Arffman, Terhi T. Piltonen, Reedik Mäg, Triin Laisk
Publié dans: Nature Communications, Numéro Vol 13, 2022, Page(s) article: 3584, ISSN 2041-1723
Éditeur: Nature Publishing Group
DOI: 10.1038/s41467-022-31188-5

Clinical Conditions and Their Impact on Utility of Genetic Scores for Prediction of Acute Coronary Syndrome

Auteurs: Jiwoo Lee, Tuomo Kiiskinen, Nina Mars, Sakari Jukarainen, Erik Ingelsson, Benjamin Neale, Samuli Ripatti, Pradeep Natarajan, and Andrea Ganna
Publié dans: Circulation: Genomic and Precision Medicine, Numéro Vol. 14, No. 4, 2021, ISSN 0009-7322
Éditeur: Lippincott Williams & Wilkins Ltd.
DOI: 10.1161/circgen.120.003283

Nationwide health, socio-economic and genetic predictors of COVID-19 vaccination status in Finland

Auteurs: Hartonen T*, Jermy B*, Sõnajalg H, Vartiainen P, Krebs K, Vabalas A, FinnGen, Estonian Biobank Research Team, Leino T, Nohynek H, Sivelä J, Mägi R, Daly MJ, Ollila HM, Milani L, Perola M, Ripatti S, Ganna A.
Publié dans: Nature Human Behaviour, Numéro Vol 7, 2023, Page(s) 1069-1083, ISSN 1476-4687
Éditeur: Nature
DOI: 10.1038/s41562-023-01591-z

COVID-19: a challenge and an opportunity

Auteurs: Alessandra Renieri
Publié dans: EJHG, Numéro Vol 30, 2022, Page(s) 870-871, ISSN 1018-4813
Éditeur: Natue Publishing Group
DOI: 10.1038/s41431-022-01142-6

The human genetic epidemiology of COVID-19

Auteurs: Mari Niemi, Mark Daly, Andrea Ganna
Publié dans: Nature Reviews: Genetics, Numéro Vol 23, 2022, Page(s) 533-546, ISSN 0028-0836
Éditeur: Nature Publishing Group
DOI: 10.1038/s41576-022-00478-5

Gain- and Loss-of-Function CFTR Alleles Are Associated with COVID-19 Clinical Outcomes

Auteurs: Margherita Baldassarri, Kristina Zguro, Valeria Tomati, Cristina Pastorino, Francesca Fava, Susanna Croci, Mirella Bruttini, Nicola Picchiotti, Simone Furini 2,GEN-COVID, Nicoletta Pedemonte, Chiara Gabbi, Alessandra Renieri, Chiara Fallerini
Publié dans: Cells, Numéro 11(24), 2022, Page(s) 4096, ISSN 2073-4409
Éditeur: MDPI
DOI: 10.3390/cells11244096

Integrating transcriptomics, metabolomics, and GWAS helps reveal molecular mechanisms for metabolite levels and disease risk

Auteurs: Xianyong Yin; Debraj Bose; Annie Kwon; Sarah C. Hanks; Anne U. Jackson; Heather M. Stringham; Ryan Welch; Anniina Oravilahti; Lilian Fernandes Silva; Adam E. Locke; Christian Fuchsberger; Susan K. Service; Michael R. Erdos; Lori L. Bonnycastle; Johanna Kuusisto; Nathan O. Stitziel; Ira M. Hall; Jean Morrison; Samuli Ripatti; Aarno Palotie; Nelson B. Freimer; Francis S. Collins; Karen L. Mohlke; La
Publié dans: AJHG, Numéro Vol 109, Numéro 10, 2022, Page(s) 1727-1741, ISSN 0002-9297
Éditeur: University of Chicago Press
DOI: 10.1016/j.ajhg.2022.08.007

Integration of questionnaire-based risk factors improves polygenic risk scores for human coronary heart disease and type 2 diabetes

Auteurs: Max Tamlander, Nina Mars, Matti Pirinen, FinnGen, Elisabeth Widén & Samuli Ripatti
Publié dans: Comm. Biology, Numéro Vol 5, 2022, Page(s) 158, ISSN 2399-3642
Éditeur: Nature
DOI: 10.1038/s42003-021-02996-0

Reducing noisy annotations for depression estimation from facial images

Auteurs: Lang He, Prayag Tiwari, Chonghua Lv, WenShuai Wu, Liyong Guo
Publié dans: Neural Networks, Numéro Vol 153, 2022, Page(s) 120-129, ISSN 0893-6080
Éditeur: Pergamon Press Ltd.
DOI: 10.1016/j.neunet.2022.05.025

Estimation of recurrent atherosclerotic cardiovascular event risk in patients with established cardiovascular disease: the updated SMART2 algorithm

Auteurs: Steven H J Hageman, Ailsa J McKay, Peter Ueda, Laura H Gunn, Tomas Jernberg, Emil Hagström, Deepak L Bhatt, Ph. Gabriel Steg, Kristi Läll, Reedik Mägi, ...Kausik K Ray, Jannick A N Dorresteijn, Frank L J Visseren on behalf of the UCC-SMART Study Group and the ESC Cardiovascular Risk Collaboration
Publié dans: European Heart Journal, Numéro 43, issue 18, 2022, Page(s) 1715-1727, ISSN 0195-668X
Éditeur: Oxford University Press
DOI: 10.1093/eurheartj/ehac056

ANGPTL8 protein-truncating variant associated with lower serum triglycerides and risk of coronary disease.

Auteurs: Pyry, Helkkula; Tuomo, Kiiskinen; Aki S, Havulinna; Juha, Karjalainen; Seppo, Koskinen; Veikko, Salomaa; Mark J, Daly; Aarno, Palotie; Ida, Surakka; Samuli, Ripatti
Publié dans: PLoS Genetics, Numéro 11, 2021, ISSN 1553-7404
Éditeur: San Francisco, CA Public Library of Science ©2005-
DOI: 10.1371/journal.pgen.1009501

Incorporating functional summary information in Bayesian neural networks using a Dirichlet process likelihood approach

Auteurs: Raj, V., Cui, T., Heinonen, M., and Marttinen, P.
Publié dans: The Proceedings of 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6741-6763. (AISTATS 2023), 2023, Page(s) PMLR 206:6741-6763
Éditeur: PMLR

Contextualized graph embeddings for adverse drug event detection

Auteurs: Gao, Y., Ji, S., Zhang, T., Tiwari, P., and Marttinen, P.
Publié dans: The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2022), 2022
Éditeur: Springer
DOI: 10.1007/978-3-031-26390-3_35

HAPNEST: An efficient tool for generating large-scale genetics datasets from limited training data

Auteurs: Sophie Wharrie, Zhiyu Yang, Vishnu Raj, Remo Monti, Rahul Gupta, Ying Wang, Alicia Martin, Luke J O'Connor, Samuel Kaski, Pekka Marttinen, Pier Palamara, Christoph Lippert, Andrea Ganna
Publié dans: NeurIPS 2022 Workshop on Synthetic Data for Empowering ML Research, 2022, Page(s) 1-7
Éditeur: NeurIPS

Causal Modeling of Policy Interventions From Treatment–Outcome Sequences

Auteurs: Hizli, C., John, S.T., Juuti, A., Saarinen, T., Pietiläinen, K., and Marttinen, P.
Publié dans: The 40th International Conference on Machine Learning (ICML 2023), 2023
Éditeur: unkonwn

Deconfounded Representation Similarity for Comparison of Neural Networks

Auteurs: Cui, T., Kumar, Y., Marttinen, P., and Kaski, S.
Publié dans: 2022, ISBN 9781713871088
Éditeur: NeurIPS Proceedings

Patient Outcome and Zero-shot Diagnosis Prediction with Hypernetwork-guided Multitask Learning

Auteurs: Ji, Shaoxiong; Marttinen, Pekka
Publié dans: The 17th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2023)., Numéro 1, 2023, Page(s) 589-598
Éditeur: EACL
DOI: 10.48550/arxiv.2109.03062

A Critical Look at the Consistency of Causal Estimation with Deep Latent Variable Models

Auteurs: Severi Rissanen, Pekka Marttinen
Publié dans: 35th Conference on Neural Information Processing Systems (NeurIPS 2021), 2021
Éditeur: NeurIPS 2021

Characterizing personalized effects of family information on disease risk using graph representation learning

Auteurs: Wharrie, S., Yang, Z., Ganna, A., & Kaski, S.
Publié dans: Proceedings of Machine Learning Research, 2023
Éditeur: unknown

A Unified Review of Deep Learning for Automated Medical Coding

Auteurs: Ji, Shaoxiong; Sun, Wei; Li, Xiaobo; Dong, Hang; Taalas, Ara; Zhang, Yijia; Wu, Honghan; Pitkänen, Esa; Marttinen, Pekka
Publié dans: J of ACM, Numéro Vol 37, no 4, article 111, 2022, ISSN 0004-5411
Éditeur: Association for Computing Machinary, Inc.
DOI: 10.48550/arxiv.2201.02797

A unified framework for estimating country-specific cumulative incidence for 18 diseases stratified by polygenic risk

Auteurs: Bradley Jermy, Kristi Läll, Brooke Wolford, Ying Wang, Kristina Zguro, Yipeng Cheng, Masahiro Kanai, Stavroula Kanoni, Zhiyu Yang, Tuomo Hartonen, Remo Monti, Julian Wanner, Omar Youssef, Estonian Biobank research team, FinnGen, Christoph Lippert, David van Heel, Yukinori Okada, Daniel L.McCartney, Caroline Hayward, Riccardo E. Marioni, Simone Furini, Alessandra Renieri, Alicia R. Martin, Benjami
Publié dans: MedRxiv, 2023, ISSN 1476-4687
Éditeur: tbc
DOI: 10.1101/2023.06.12.23291186

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