Results 91 to 100 of about 19,696,345 (257)

Discriminant analysis of multivariate time series using wavelets [PDF]

In analyzing ECG data, the main aim is to differentiate between the signal patterns of those of healthy subjects and those of individuals with specific heart conditions.
M. Andrés Alonso, Ann Elizabeth Maharaj
core  

On the comparison of time series using subsampling [PDF]

, 2005
In this paper we propose a procedure based on the subsampling techniques for the comparison of stationary time series that are not necessarily independent.
Maharaj, Elizabeth Ann, Alonso Fernández, Andrés Modesto   +1 more
core   +1 more source

Intrapatient tumour heterogeneity and clonal evolution in an autopsy study of metastatic salivary gland cancer

Molecular Oncology, EarlyView.
Tumour heterogeneity and clonal evolution of metastatic salivary gland cancer were evaluated in two patients with adenoid carcinoma and one patient with myoepithelial carcinoma. Radiology‐guided autopsy enabled multi‐region sampling (total samples n = 149), followed by whole‐genome sequencing and phylogenetic reconstruction (17 tumour samples, 4–7 per ...
Gerben Lassche, Niels J. van Ruitenbeek, Charlotte Adang, Luke O'Gorman, Pui Yuen Lee, Willemijn M. Klein, Adriana C. H. van Engen‐van Grunsven, Jack A. Schalken, Sander Bervoets, Gerald W. Verhaegh, Carla M. L. van Herpen   +10 more
wiley   +1 more source

Extracellular vesicle lipidomics liquid biopsy reveals systemic and tumor microenvironment metabolic reprogramming in ovarian cancer

Molecular Oncology, EarlyView.
Extracellular vesicle (EV) lipidomic profiling of plasma and ascites from patients with high‐grade serous ovarian cancer and of ovarian cancer cell lines reveals enrichment of triglycerides (TGs), diacylglycerols (DGs), phosphatidylcholine (PCs), sphingomyelins (SMs), reflecting tumor metabolic reprogramming.
Shikha Rani, Dominic Guanzon, Andrew Lai, Katherin Scholz‐Romero, Sarah Reed, Edita Ritmejeryte, Rohan Lourie, Naven Chetty, Kaltin Ferguson, Carlos Salomon   +9 more
wiley   +1 more source

TATS: toolbox for time series data augmentation [PDF]

PeerJ Computer Science
Augmenting time series data plays a crucial role in enhancing the generalization of classification models, especially in scenarios where labeled datasets are limited.
Dawid Warchoł, Mariusz Oszust
doaj   +2 more sources

Patient risk stratification for hospital-associated C. diff as a time-series classification task

, 2019
A patient's risk for adverse events is affected by temporal processes including the nature and timing of diagnostic and therapeutic activities, and the overall evolution of the patient's pathophysiology over time.
Horvitz, Eric, Guttag, John V, Wiens, Jenna Anne Marleau   +2 more
core  

Unique circulating miRNAome signatures captured with distinct molecular states in Lynch syndrome and sporadic colorectal cancer

Molecular Oncology, EarlyView.
Circulating microRNA profiles distinguish nonmalignant Lynch syndrome from cancer‐associated Lynch syndrome, sporadic colorectal cancer, and healthy controls. Age‐stratified analysis reveals disease‐specific regulatory states, and a six‐miRNA panel shows concordant separation in an independent colorectal tissue cohort.
Ramadhani Salum Chambuso, Md Shohel Ul Islam, Rosa M Xicola, Raj Ramesar, Xavier Llor, Sinclair Steele   +5 more
wiley   +1 more source

Data Augmentation with Suboptimal Warping for Time-Series Classification

Sensors, 2019
In this paper, a novel data augmentation method for time-series classification is proposed. In the introduced method, a new time-series is obtained in warped space between suboptimally aligned input examples of different lengths.
Krzysztof Kamycki, Tomasz Kapuscinski, Mariusz Oszust   +2 more
doaj   +1 more source

Targeting the EpCAM‐AXL axis to overcome drug resistance in lung cancer

Molecular Oncology, EarlyView.
Lung cancer cells often evade therapy by hijacking signaling pathways. We reveal that cleaved EpCAM (sEpCAM) stabilizes the oncogenic protein AXL, driving NF‐κB and STAT3‐mediated chemoresistance. This EpCAM‐AXL axis identifies a high‐risk patient subset with poor prognosis.
Alexa Guerrero‐Alba, Mark Shacker, Timothy P. Fleming, Michael A. Smith, Ross M. Bremner, Narendra V. Sankpal   +5 more
wiley   +1 more source

Scalable and Explainable Time Series Classification

, 2022
© 2022 Nestor Stiven Cabello WilsonTime series data are ubiquitous, and the explosion of sensor technologies on industry applications has further accelerated their growth.
Cabello Wilson, Nestor Stiven
core   +1 more source