Results 51 to 60 of about 576,901 (299)

Non-Parametric Time Series Classification [PDF]

Proceedings of the 2005 IEEE International Conference on Robotics and Automation, 2006
We present an improved state-based prediction algorithm for time series. Given time series produced by a process composed of different underlying states, the algorithm predicts future time series values based on past time series values for each state. Unlike many algorithms, this algorithm predicts a multi-modal distribution over future values.
Scott Lenser, Manuela M. Veloso
openaire   +1 more source

Deep Sequencing of FLT3‐ITD Enables Response Evaluation and Post‐Treatment Monitoring in Childhood AML: An Exploratory Study

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background An internal tandem duplication in the gene encoding Fms‐like tyrosine kinase 3 (FLT3‐ITD) is associated with high relapse risk and poor prognosis in acute myeloid leukemia (AML) and plays a crucial role in treatment decisions. Measurable residual disease (MRD) analysis of FLT3‐ITD during and after treatment has shown prognostic ...
Sofie Johansson Alm, Bea Tornberg, Erik Delsing Malmberg, Henrik Hasle, Kristian Løvvik Juul‐Dam, Lars Palmqvist, Borhan R. Saeed, Giti Shah Barkhordar, Anastasia Soboli, Anna Staffas, Jonas Abrahamsson, Linda Fogelstrand   +11 more
wiley   +1 more source

Polarization of forecast densities : a new approach to time series classification

, 2014
Time series classification has been extensively explored in many fields of study. Most methods are based on the historical or current information extracted from data.
Inder, Brett, Maharaj, Elizabeth Ann, Liu, Shen   +2 more
core   +1 more source

Therapeutic Apheresis for Intravenous Methylprednisolone‐Refractory Neuromyelitis Optica Spectrum Disorder: Clinical and Radiological Outcomes in a Single‐Center Case Series

Therapeutic Apheresis and Dialysis, EarlyView.
ABSTRACT Background Neuromyelitis optica spectrum disorder (NMOSD) is a relapsing autoimmune disease of the central nervous system. High‐dose intravenous methylprednisolone (IVMP) is the standard first‐line therapy for acute attacks, although some patients remain refractory.
Wataru Horiguchi, Daisuke Katagiri, Takeyuki Watadani, Shunichi Matsuda, Hiroshi Kaneko, Noritoshi Arai   +5 more
wiley   +1 more source

LSTM Fully Convolutional Networks for Time Series Classification

IEEE Access, 2018
Fully convolutional neural networks (FCNs) have been shown to achieve the state-of-the-art performance on the task of classifying time series sequences.
Fazle Karim, Somshubra Majumdar, Houshang Darabi, Shun Chen   +3 more
doaj   +1 more source

TEASER: early and accurate time series classification [PDF]

, 2020
Early time series classification (eTSC) is the problem of classifying a time series after as few measurements as possible with the highest possible accuracy.
Schäfer, Patrick, Leser, Ulf
core   +1 more source

Therapeutic Apheresis in Nigeria: A Multi‐Center Summary of Abstracts From the Inaugural Nigerian Society for Apheresis Scientific Meeting

Therapeutic Apheresis and Dialysis, EarlyView.
ABSTRACT Background Therapeutic apheresis (TA) is an established treatment modality for hematologic, neurologic, and immunologic disorders, yet access remains severely limited in sub‐Saharan Africa. Donor apheresis, including platelet apheresis collection from healthy donors, represents an important complementary modality supporting blood product ...
Nosa Bazuaye, Chimezie Okwuonu, Evelyn Idam, Folasade Adelekan‐Popoola, Shakirat Gold‐Olufadi, Olufunto Olufela Kalejaiye, Abdullateef Ogala, Zinnah Aloziem, Blossom Amamchukwu, Patience Elimia, Mkpoikanabasi Obot‐Obot, Henry Mbakwe, Praises Maduagwuna, Olatunji Akinrodoye, Chiamaka Anyanwu, Benjamin Anyanwu, Adedamola Akinsiku, Oluwatoyin A. Akinsiku, Muzamil O. Hassan, Fatiu A. Arogundade, Olalekan E. Ojo, Homayemem Weli, Jesupelumi Adenihun, Aderemi Adelaja, Ebun Bamgboye, Olalekan Olatise, Ade E. Faponle, Ayoola Odeyemi, Michael Muoka, Stephen Asaolu, Qudrat Busari, Blessing Dawudu, Michael Naiyeju, Rasheed A. Balogun   +33 more
wiley   +1 more source

Sparseness-Optimized Feature Importance for Time Series Classification

IEEE Access
The literature reports a wide variety of attribution methods for explaining the predictions made by time series classification (TSC) algorithms. These post-hoc explanation methods span from model-specific to agnostic procedures that operate at different ...
Isel Grau, Gonzalo Napoles, Agnieszka Jastrzebska, Yamisleydi Salgueiro   +3 more
doaj   +1 more source

Similarity Learning for Time Series Classification

CoRR, 2016
Multivariate time series naturally exist in many fields, like energy, bioinformatics, signal processing, and finance. Most of these applications need to be able to compare these structured data. In this context, dynamic time warping (DTW) is probably the most common comparison measure. However, not much research effort has been put into improving it by
Maria-Irina Nicolae, Éric Gaussier, Amaury Habrard, Marc Sebban   +3 more
openaire   +2 more sources

Using derivatives in time series classification [PDF]

Data Mining and Knowledge Discovery, 2012
Over recent years the popularity of time series has soared. Given the widespread use of modern information technology, a large number of time series may be collected during business, medical or biological operations, for example. As a consequence there has been a dramatic increase in the amount of interest in querying and mining such data, which in ...
Tomasz Górecki, Maciej Luczak
openaire   +1 more source