Results 171 to 180 of about 576,901 (299)

PIP: Pictorial Interpretable Prototype Learning for Time Series Classification. [PDF]

IEEE Comput Intell Mag, 2022
Ghods A, Cook DJ.
europepmc   +1 more source

Integration of Serum Neurofilament Light Chain and Cortical Dysfunction Improves Diagnostic Accuracy in ALS

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To determine whether integration of serum neurofilament light chain (NfL) and cortical dysfunction improves diagnostic accuracy in amyotrophic lateral sclerosis (ALS) when applied alongside the Gold Coast criteria (GCC). Methods In this prospective study, 148 participants with suspected ALS were recruited (101 ALS and 47 with ALS ...
Aicee Dawn Calma, Nathan Pavey, Yukiko Tsuji, Amirul Ab Ghapar, Mehdi A.J. van den Bos, Bronwen Orden, Grace Lee, Linda Mekhael, Julie Ryder, Cláudia Santos Silva, David McDonald, Fakhria Kakar, Con Yiannikas, Matthew C. Kiernan, David A. Brown, Parvathi Menon, Steve Vucic   +16 more
wiley   +1 more source

Horizontal nystagmus identification with joint SAM segmentation and time series classification. [PDF]

Eur Arch Otorhinolaryngol
Lin C, Yang H, Wu H, Xu M, Yang R, Zhu Z.   +5 more
europepmc   +1 more source

Decoupled Early Time Series Classification Using Varied-Length Feature Augmentation and Gradient Projection Technique. [PDF]

Entropy (Basel), 2022
Chen H, Zhang Y, Tian A, Hou Y, Ma C, Zhou S.   +5 more
europepmc   +1 more source

Integrating Time‐Adjusted Imaging Instability Into Functional Outcome Prediction After Intracerebral Hemorrhage: Development and Validation of the HAGIV Score

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Early risk stratification may support clinical decision‐making in spontaneous intracerebral hemorrhage (ICH). We aimed to develop and internally validate HAGIV, a score integrating frequency of imaging markers (FIM), a time‐adjusted non‐contrast computed tomography (CT) metric of hematoma expansion, with established predictors for 90‐
Lei Song, Ren Ke, Anqi Chen, Yufei Fu, Hang Zhou, Rujia Wang, Liwei Zou, Yongqiang Yu, Ming Yuan, Xiaoming Qiu, Mengzhou Xue   +10 more
wiley   +1 more source

A Comprehensive Explanation Framework for Biomedical Time Series Classification. [PDF]

IEEE J Biomed Health Inform, 2021
Ivaturi P, Gadaleta M, Pandey AC, Pazzani M, Steinhubl SR, Quer G.   +5 more
europepmc   +1 more source

On Multivariate Financial Time Series Classification

CoRR
This article investigates the use of Machine Learning and Deep Learning models in multivariate time series analysis within financial markets. It compares small and big data approaches, focusing on their distinct challenges and the benefits of scaling. Traditional methods such as SVMs are contrasted with modern architectures like ConvTimeNet.
openaire   +2 more sources

Time-Series Classification: Technique Development and Empirical Evaluation

, 2002
Many interesting applications involve decision prediction based on a time-series sequence or a set of time-series sequences, which are referred to as time-series classification problems.
Yang, Ching-Ting
core  

Long‐Term Neurologic Exam Findings in People Diagnosed and Treated During Acute HIV Infection

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Evaluate clinical and laboratory correlates of abnormal neurologic exam findings after acute HIV infection (AHI). Methods Participants from the RV254/SEARCH 010 cohort in Bangkok underwent standardized neurologic examinations at Weeks 0 (AHI), 12, 96, and 288 following antiretroviral therapy (ART).
Kathryn B. Holroyd, Tyler Hamby, Carlo Sacdalan, Somchai Sriplienchan, Pathariya Promensa, Luxenaree Poonpitak, Netsiri Dumrongpisutikul, Eugène Kroon, Sandhya Vasan, Robert Paul, Ferron O'Campo, Lydie Trautmann, Phillip Chan, Serena Spudich, on behalf of the RV254/SEARCH 010 Study Team, Julie Ake, Sandhya Vasan, Lydie Trautmann, Merlin Robb, Trevor Crowell, Donn Colby, Diane Bolton, Shelly Krebs, Leigh Ann Eller, Morgane Rolland, Rasmi Thomas, Dominic Paquin Proulx, Suteeraporn Pinyakorn, Tyler Hamby, Mark de Souza, Ellen Turk, Amber Moodley, Gerald Quarles, Jintanat Ananworanich, Denise Hsu, Victoria Polonis, Nelson Michael, Sheila Peel, COL Eric Garges, Alexandra Schuetz, Siriwat Akapirat, Bessara Nantapinit, Pornsuk Visudhiphan, Saowanit Getchalarat, Nampueng Churikanont, Sangsulee Thamakaison, Somchai Sriplienchan, Carlo Sacdalan, Pathariya Promsena, Luxe‐naree Poonpitak, Eugene Kroon, Nitiya Chomchey, Jintana Intasan, Varaporn Pothipala, Ferron Ocampo, Nittaya Phanuphak, Nipat Teeratakulpisan, Yuwaree Pichitchok, Anchalee Avihingsanon, Opass Putcharoen, Kiat Ruxrungtham, Thanyawee Puthanakit, Sopark Manasnayakorn, Phandee Watanaboonyongcharoen, Rungsun Rerknimitr, Irini Sereti, Daniel Douek, Eli Bortiz, Frank Maldarelli, Mary Kearney, Serena Spudich, Phillip Chan, Lishomwa Ndhlovu, Guinevere Li, Michael Corley, Victor Valcour, Peter Hunt, Jacob Estes, Afam Okoye, Jeff Lifson, Claire Deleage, Nicolas Chomont, Andres Finzi, Lyle McKinnon, Henrik Zetterberg, Robert Siliciano, Robert Paul, Julie Mannarino, Jonathan Li, John Mellors, Josh Cytkor, Dan Barouch, Michael Seaman, Boris Juelg, Alex Shalek, Timothy Schacker, Ashley Haase, Mario Stevenson, Wenjun Li, Arthur Kim, Sharon Lewin, Adam Carrico, Susana Valente, Fred Hutchinson, Josh Schiffer, Guido Ferrari, Beau Ances, Alberto Bosque, Katharine Bar, Killian Pohl, David Ho, Yaoxing Huang, Michael Busch, Mohamed Abdel‐Mohsen, Johanna Gostner, Brian Agan, Fatah Kashanchi, Greg Laird, Kathryn Holroyd   +118 more
wiley   +1 more source

EffiShapeFormer: Shapelet-Based Sensor Time Series Classification with Dual Filtering and Convolutional-Inverted Attention. [PDF]

Sensors (Basel)
Bao J, Wang S, Tang X, Zhang S, Wang H, Wang L, Zhang Q, Wu N, Yang X, Zhang X, Li X, Liao J, Liu L.   +12 more
europepmc   +1 more source