Zobrazeno 1 - 10
of 30
pro vyhledávání: '"Anton Schwaighofer"'
Autor:
Kenza Bouzid, Harshita Sharma, Sarah Killcoyne, Daniel C. Castro, Anton Schwaighofer, Max Ilse, Valentina Salvatelli, Ozan Oktay, Sumanth Murthy, Lucas Bordeaux, Luiza Moore, Maria O’Donovan, Anja Thieme, Aditya Nori, Marcel Gehrung, Javier Alvarez-Valle
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-15 (2024)
Abstract Timely detection of Barrett’s esophagus, the pre-malignant condition of esophageal adenocarcinoma, can improve patient survival rates. The Cytosponge-TFF3 test, a non-endoscopic minimally invasive procedure, has been used for diagnosing in
Externí odkaz:
https://doaj.org/article/a7d26ad27adf4210ba573b93bfdee22b
Autor:
Mélanie Bernhardt, Daniel C. Castro, Ryutaro Tanno, Anton Schwaighofer, Kerem C. Tezcan, Miguel Monteiro, Shruthi Bannur, Matthew P. Lungren, Aditya Nori, Ben Glocker, Javier Alvarez-Valle, Ozan Oktay
Publikováno v:
Nature Communications, Vol 13, Iss 1, Pp 1-11 (2022)
High quality labels are important for model performance, evaluation and selection in medical imaging. As manual labelling is time-consuming and costly, the authors explore and benchmark various resource-effective methods for improving dataset quality
Externí odkaz:
https://doaj.org/article/70d06a2166804fea9694afa4ba328c23
An overview of recent efforts in the machine learning community to deal with dataset and covariate shift, which occurs when test and training inputs and outputs have different distributions.Dataset shift is a common problem in predictive modeling tha
Autor:
Benedikt Boecking, Naoto Usuyama, Shruthi Bannur, Daniel C. Castro, Anton Schwaighofer, Stephanie Hyland, Maria Wetscherek, Tristan Naumann, Aditya Nori, Javier Alvarez-Valle, Hoifung Poon, Ozan Oktay
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031200588
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::907f669f41e07274f962a309a9855503
https://doi.org/10.1007/978-3-031-20059-5_1
https://doi.org/10.1007/978-3-031-20059-5_1
Autor:
Mélanie Bernhardt, Daniel C. Castro, Ryutaro Tanno, Anton Schwaighofer, Kerem C. Tezcan, Miguel Monteiro, Shruthi Bannur, Matthew P. Lungren, Aditya Nori, Ben Glocker, Javier Alvarez-Valle, Ozan Oktay
Publikováno v:
Nature communications. 13(1)
Imperfections in data annotation, known as label noise, are detrimental to the training of machine learning models and have an often-overlooked confounding effect on the assessment of model performance. Nevertheless, employing experts to remove label
Autor:
Anton Schwaighofer, Aditya V. Nori, Melissa Bristow, Ryutaro Tanno, Ozan Oktay, David J. Noble, Christopher M. Bishop, Gill Barnett, Kenton O'Hara, David Carter, Ben Glocker, Jay Nanavati, Javier Alvarez-Valle, Rajesh Jena, Yvonne Rimmer
Publikováno v:
JAMA Network Open. 3:e2027426
Importance Personalized radiotherapy planning depends on high-quality delineation of target tumors and surrounding organs at risk (OARs). This process puts additional time burdens on oncologists and introduces variability among both experts and insti
Publikováno v:
Combinatorial Chemistry and High Throughput Screening
Combinatorial Chemistry and High Throughput Screening, Bentham Science Publishers, 2009, 12 (5), pp.453-468. ⟨10.2174/138620709788489064⟩
Combinatorial Chemistry and High Throughput Screening, Bentham Science Publishers, 2009, 12 (5), pp.453-468. ⟨10.2174/138620709788489064⟩
A large number of different machine learning methods can potentially be used for ligand-based virtual screening. In our contribution, we focus on three specific nonlinear methods, namely support vector regression, Gaussian process models, and decisio
Autor:
Antonius Ter Laak, Nikolaus Heinrich, Timon Schroeter, Klaus-Robert Müller, Sebastian Mika, Detlev Suelzle, Ursula Ganzer, Anton Schwaighofer
Publikováno v:
Journal of Computer-Aided Molecular Design. 21:651-664
We investigate the use of different Machine Learning methods to construct models for aqueous solubility. Models are based on about 4000 compounds, including an in-house set of 632 drug discovery molecules of Bayer Schering Pharma. For each method, we
Publikováno v:
IEEE Transactions on Knowledge and Data Engineering. 16:56-69
Memory-based collaborative filtering (CF) has been studied extensively in the literature and has proven to be successful in various types of personalized recommender systems. In this paper, we develop a probabilistic framework for memory-based CF (PM
Autor:
Gerhard A. Müller, Kay-Geert A. Hermann, Volker Tresp, Marina Backhaus, Alexander D. Klose, Alexander K. Scheel, Uwe J. Netz, Anton Schwaighofer, Gerd R Burmester, Andreas H. Hielscher
Publikováno v:
Medical Laser Application. 18:198-205
Summary Rheumatoid arthritis (RA) is the most frequent chronic inflammatory arthropathy that often leads to joint destruction. Essential for the progress of the disease are both an early diagnosis and a sensitive follow-up of synovitis. In this paper