Results 71 to 80 of about 293,798 (360)
This study presents a novel AI‐based diagnostic approach—comprehensive serum glycopeptide spectra analysis (CSGSA)—that integrates tumor markers and enriched glycopeptides from serum. Using a neural network model, this method accurately distinguishes liver and pancreatic cancers from healthy individuals.
Motoyuki Kohjima+6 more
wiley +1 more source
Introduction. When developing and testing high-speed communication links of digital electronic devices, the pulse shape of electrical signals and interference in transmission lines is commonly controlled using eye diagrams.
Yu. V. Kuznetsov+3 more
doaj +1 more source
Decrypting cancer's spatial code: from single cells to tissue niches
Spatial transcriptomics maps gene activity across tissues, offering powerful insights into how cancer cells are organised, switch states and interact with their surroundings. This review outlines emerging computational, artificial intelligence (AI) and geospatial approaches to define cell states, uncover tumour niches and integrate spatial data with ...
Cenk Celik+4 more
wiley +1 more source
Blind Source Separation for Convolutive Mixtures with Neural Networks
Blind source separation of convolutive mixtures is used as a preprocessing stage in many applications. The aim is to extract individual signals from their mixtures.
KIREI, B. S.+4 more
doaj +1 more source
Using multi‐omic characterization, we aimed to identify key regulators specific to squamous cell lung carcinoma (SqCC). SqCC‐specific differentially expressed genes were integrated with metabolics data. High expression of the creatine transporter SLC6A8, along with elevated creatine levels, appeared to be a distinct metabolic feature of SqCC.
Johan Staaf+10 more
wiley +1 more source
Research on multi-target recognition method based on WSN and blind source separation
Aiming at the problem of signal aliasing in multi-target detection and recognition using wireless sensor network (WSN),a blind source separation algorithm was proposed,which can determine the number of targets and obtain the accurate source signals.In ...
Pengju HE, Gangyi LIU, Siyi LIU
doaj +2 more sources
On the INFOMAX algorithm for blind signal separation
This paper provides an analytical examination of the INFOMAX algorithm and establishes its effectiveness for blind signal separation using extensive simulation results. Results obtained show that the INFOMAX is not able to separate signal sources unless signal pre-processing is carried-out whereby the data to train the separating matrix is decorrelated.
Joe F. Chicharo+3 more
openaire +3 more sources
Blind Separation of Underwater Acoustic Signals [PDF]
In last two decades, many researchers have been involved in acoustic tomography applications. Recently, few algorithms have been dedicated to the passive acoustic tomography applications in a single input single output channel. Unfortunately, most of these algorithms can not be applied in a real situation when we have a Multi-Input Multi-Output channel.
Ali Mansour+2 more
openaire +2 more sources
Efficient independent component analysis
Independent component analysis (ICA) has been widely used for blind source separation in many fields such as brain imaging analysis, signal processing and telecommunication.
Bickel, Peter J., Chen, Aiyou
core +2 more sources
ABSTRACT Objective Spinal muscular atrophy (SMA) significantly impacts motor function. This study aimed to assess the persistent burden and unmet needs among currently treated patients with SMA and their caregivers. Methods Two complementary web‐based surveys were distributed in August 2024 among patients with SMA and their caregivers.
Julie A. Parsons+8 more
wiley +1 more source