Results 41 to 50 of about 851,309 (264)

Statistical topological data analysis using persistence landscapes [PDF]

, 2015
We define a new topological summary for data that we call the persistence landscape. Since this summary lies in a vector space, it is easy to combine with tools from statistics and machine learning, in contrast to the standard topological summaries ...
Bubenik, Peter
core  

ICU‐EEG Pattern Detection by a Convolutional Neural Network

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Patients in the intensive care unit (ICU) often require continuous EEG (cEEG) monitoring due to the high risk of seizures and rhythmic and periodic patterns (RPPs). However, interpreting cEEG in real time is resource‐intensive and heavily relies on specialized expertise, which is not always available.
Giulio Degano, Hervé Quintard, Andreas Kleinschmidt, Nikita Francini, Oana E. Sarbu, Pia De Stefano   +5 more
wiley   +1 more source

Towards a New Science of a Clinical Data Intelligence [PDF]

, 2013
In this paper we define Clinical Data Intelligence as the analysis of data generated in the clinical routine with the goal of improving patient care. We define a science of a Clinical Data Intelligence as a data analysis that permits the derivation of ...
Budde, Klemens, Cavallaro, Alexander, Costa, Maria J., Daumke, Philipp, Fasching, Peter A., Ganslandt, Thomas, Hinrichs, Carl, Huang, Yi, Krompass, Denis, Oppelt, Patricia G., Reis, Andre, Schmidt, Danilo, Sedlmayr, Martin, Sonntag, Daniel, Tresp, Volker, Wittenberg, Thomas, Zillner, Sonja   +16 more
core  

Proof-Pattern Recognition and Lemma Discovery in ACL2

, 2013
We present a novel technique for combining statistical machine learning for proof-pattern recognition with symbolic methods for lemma discovery. The resulting tool, ACL2(ml), gathers proof statistics and uses statistical pattern-recognition to pre ...
B. Buchberger, D. Kühlwein, E. Komendantskaya, J. Denzinger, J. Urban, K. Claessen, K. Claessen, M. Johansson, O. Montano-Rivas, R.L. McCasland, S. Colton, S. Hetzl   +11 more
core   +1 more source

Hip morphology‐based osteoarthritis risk prediction models: development and external validation using individual participant data from the World COACH Consortium

Arthritis Care &Research, Accepted Article.
Objectives This study aims to develop hip morphology‐based radiographic hip osteoarthritis (RHOA) risk prediction models and investigates the added predictive value of hip morphology measurements and the generalizability to different populations. Methods We combined data from nine prospective cohort studies participating in the World COACH consortium ...
Myrthe A. van den Berg, Fleur Boel, Michiel M.A. van Buuren, Noortje S. Riedstra, Jinchi Tang, Harbeer Ahedi, Nigel K. Arden, Sita M.A. Bierma‐Zeinstra, Cindy G. Boer, Flavia M. Cicuttini, Timothy F. Cootes, David T. Felson, Willem Paul Gielis, Joshua Heerey, Graeme Jones, Stefan Kluzek, Nancy E. Lane, Claudia Lindner, Joyce B.J. van Meurs, Andrea Mosler, Amanda E. Nelson, Michael C. Nevitt, Edwin H. Oei, Jos Runhaar, Harrie Weinans, Jesse H. Krijthe, Rintje Agricola   +26 more
wiley   +1 more source

Scaling-up Empirical Risk Minimization: Optimization of Incomplete U-statistics [PDF]

, 2016
In a wide range of statistical learning problems such as ranking, clustering or metric learning among others, the risk is accurately estimated by $U$-statistics of degree $d\geq 1$, i.e.
Bellet, Aurélien, Clémençon, Stéphan, Colin, Igor   +2 more
core   +2 more sources

Exploring patients’ profiles associated with the resolution of acute calcium pyrophosphate arthritis treatedwith colchicine and prednisone: post hoc analysis of a randomized controlled trial

Arthritis Care &Research, Accepted Article.
Objective The objective was to identify factors determining acute arthritis resolution and safety with colchicine and prednisone in acute calcium pyrophosphate (CPP) crystal arthritis. Methods We conducted a post hoc analysis of the COLCHICORT trial, which compared colchicine and prednisone for the treatment of acute CPP crystal arthritis, using a ...
Tristan Pascart, Laurène Norberciak, Pascal Richette, Pierre Robinet, Aurore Pacaud, Gauthier Marchasson, Thibault Rabin, Hélène Luraschi, Pierre Maciejasz, Anne‐France Georgel, Augustin Latourte, Hang‐Korng Ea, Sébastien Ottaviani, Charlotte Jauffret, Vincent Ducoulombier   +14 more
wiley   +1 more source

Data‐driven forecasting of ship motions in waves using machine learning and dynamic mode decomposition

International Journal of Adaptive Control and Signal Processing, EarlyView.
Summary Data‐driven forecasting of ship motions in waves is investigated through feedforward and recurrent neural networks as well as dynamic mode decomposition. The goal is to predict future ship motion variables based on past data collected on the field, using equation‐free approaches.
Matteo Diez, Mauro Gaggero, Andrea Serani   +2 more
wiley   +1 more source

Predicting Cervical Cancer Outcomes: Statistics, Images, and Machine Learning [PDF]

, 2021
Wei Luo
openalex   +1 more source

Statistics and Machine Learning Experiments in Poetry

Sci, 2020
This paper presents a quantitative approach to poetry, based on the use of several statistical measures (entropy, information energy, N-gram, etc.) applied to a few characteristic English writings. We found that English language changes its entropy as time passes, and that entropy depends on the language used and on the author.
openaire   +2 more sources