Results 91 to 100 of about 1,645,295 (287)

Convolutional neural networks for computer-aided detection or diagnosis in medical image analysis: An overview.

Mathematical biosciences and engineering : MBE, 2019
Computer-aided detection or diagnosis (CAD) has been a promising area of research over the last two decades. Medical image analysis aims to provide a more efficient diagnostic and treatment process for the radiologists and clinicians.
Jun Gao, Qian Jiang, Bo Zhou, Daozheng Chen   +3 more
semanticscholar   +1 more source

EMT‐associated bias in the Parsortix® system observed with pancreatic cancer cell lines

Molecular Oncology, EarlyView.
The Parsortix® system was tested for CTC enrichment using pancreatic cancer cell lines with different EMT phenotypes. Spike‐in experiments showed lower recovery of mesenchymal‐like cells. This was confirmed with an EMT‐inducible breast cancer cell line.
Nele Vandenbussche, Renske Imschoot, Béatrice Lintermans, Lode Denolf, Joachim Taminau, Charlotte Fieuws, Geert Berx, Kris Gevaert, Kathleen B. M. Claes   +8 more
wiley   +1 more source

Machine learning for identifying liver and pancreas cancers through comprehensive serum glycopeptide spectra analysis: a case‐control study

Molecular Oncology, EarlyView.
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, Yuko Takami, Ken Kawabe, Kazuhiro Tanabe, Chihiro Hayashi, Mikio Mikami, Tetsuya Kusumoto   +6 more
wiley   +1 more source

Improving Accuracy of Intravoxel Incoherent Motion Reconstruction using Kalman Filter in Combination with Neural Networks: A Simulation Study [PDF]

Journal of Biomedical Physics and Engineering
Background: The intravoxel Incoherent Motion (IVIM) model extracts perfusion map and diffusion coefficient map using diffusion-weighted imaging. The main limitation of this model is inaccuracy in the presence of noise.Objective: This study aims to ...
Sam Sharifzadeh Javidi, Reza Ahadi, Hamidreza Saligheh Rad   +2 more
doaj   +1 more source

Global exponential stability and existence of almost periodic solutions in distribution for Clifford-valued stochastic high-order Hopfield neural networks with time-varying delays

AIMS Mathematics, 2022
In this paper, we consider a class of Clifford-valued stochastic high-order Hopfield neural networks with time-varying delays whose coefficients are Clifford numbers except the time delays.
Nina Huo, Bing Li, Yongkun Li
doaj   +1 more source

Decrypting cancer's spatial code: from single cells to tissue niches

Molecular Oncology, EarlyView.
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, Shi Pan, Eloise Withnell, Hou Wang Lam, Maria Secrier   +4 more
wiley   +1 more source

Object Detection: Training From Scratch

IEEE Access, 2020
The development of deep neural networks has driven the development of computer vision. Deep neural networks play an important role in object detection. To improve network performance, before using neural networks for object detection, they are commonly ...
Kai Zhao, Yan Zhou, Xin Chen
doaj   +1 more source

On the computational efficiency of symmetric neural networks

Theoretical Computer Science, 1989
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire   +2 more sources

Investigating the cell of origin and novel molecular targets in Merkel cell carcinoma: a historic misnomer

Molecular Oncology, EarlyView.
This study indicates that Merkel cell carcinoma (MCC) does not originate from Merkel cells, and identifies gene, protein & cellular expression of immune‐linked and neuroendocrine markers in primary and metastatic Merkel cell carcinoma (MCC) tumor samples, linked to Merkel cell polyomavirus (MCPyV) status, with enrichment of B‐cell and other immune cell
Richie Jeremian, Sriraam Sivachandran, Melissa Galati, Brandon Ramchatesingh, Hibo Rijal, Johnny Hanna, Elena Netchiporouk, May Chergui, Margaret Redpath, Samy Abou Setah, Ivan V. Litvinov   +10 more
wiley   +1 more source

Artificial neural networks and computer image analysis in the evaluation of selected quality parameters of pea seeds [PDF]

E3S Web of Conferences, 2019
The aim of the study was to develop an innovative method of modelling the process of evaluating the quality of agricultural crops on the basis of computer image analysis and artificial neural networks (ANN).
Szwedziak Katarzyna
doaj   +1 more source