Search results for "Neural"
showing 10 items of 2783 documents
Time-course evaluation of survival and treatment in FIRE-3 trial (AIO KRK0306).
2016
3528Background: To investigate overall survival (OS) differences in FIRE-3 in context of exposure to treatments (i.e. first-, second-, third-line) in time course. Methods: We compared OS in FIRE-3 ...
Expression of cell cycle markers and human papillomavirus infection in oral squamous cell carcinoma: use of fuzzy neural networks.
2005
Our aim was to evaluate in oral squamous cell carcinoma (OSCC) the relationship between some cell cycle markers and HPV infection, conditionally to age, gender and certain habits of patients, and to assess the ability of fuzzy neural networks (FNNs) in building up an adequate predictive model based on logic inference rules. Eighteen cases of OSCC were examined by immunohistochemistry for MIB-1, PCNA and survivin expression; presence of HPV DNA was investigated in exfoliated oral mucosa cells by nested PCR (nPCR, MY09-MY11/GP5-GP6), and HPV genotype was determined by direct DNA sequencing. Data were analyzed by traditional statistics (TS) and FNNs. HPV DNA was found in 9/18 OSCCs (50.0 %) wi…
Prognostic value of the immunohistochemical expression of vascular endothelial growth factors in malignant salivary gland neoplasms: a systematic rev…
2020
Background The immunohistochemical expression of vascular endothelial growth factor is a prognostic marker in several cancer types. In salivary gland tumors, the association between vascular endothelial growth factor and prognosis remains unclear. The purpose of this study was to perform a systematic review and meta-analysis to assess whether the immunohistochemical expression of vascular endothelial growth factor in patients with salivary gland neoplasms presents prognostic value. Material and Methods Immunohistochemical studies assessing the predictive value of vascular endothelial growth factor in salivary gland neoplasms were systematically reviewed using PubMed, Scopus, Embase, Cochran…
The use of neural networks in identifying risk factors for lymph node metastasis and recommending management of t1b esophageal cancer.
2012
The objective of this study was to establish a prediction model of lymph node status in T1b esophageal carcinoma and define the best squamous and adenocarcinoma predictors. The literature lacks a satisfactory level of evidence of T1b esophageal cancer management. We performed an analysis pooling the effects of outcomes of 2098 patients enrolled into 37 retrospective studies using “neural networks” as data mining techniques. The percentages for lymph node, lymphatic (L1), and vascular (V1) invasion in Sm1 esophageal cancers were 24, 46, and 20 per cent, respectively. The same parameters apply to Sm2 with 34, 63, and 38 per cent as opposed to Sm3 with 51, 69, and 47 per cent. The respective …
Factors related to early castration resistance in metastatic prostate cancer. Results from the National Prostate Cancer Registry in Spain
2019
Abstract Introduction The objective of the study was to determine the factors independently related with the development of castration resistance (CR) in prostate cancer (PC) in the medium term. Material and methods 155 patients diagnosed with metastatic PC with a follow-up of up to 39 months. Data taken from the National PC Registry. The evaluated variables were age, PSA, nadir PSA, Gleason, perineural invasion, TNM stages, and ADT type (intermittent / continuous). Results Mean follow-up 26,2 ± 13,4 months. 47.1% developed early CR, with mean time until onset of 12,2 ± 8,7 months. Univariate analysis: the mean PSA was correlated with CR (290 ± 905,1 ng/mL in non CR, 519,1 ± 1437,2 ng/mL in…
Analysis of the road traffic management system in the neural network development perspective
2019
The research goal of the paper is to present the issues connected with road traffic management systems and to illustrate a management system that uses Intelligent Transportation Systems and neural networks. The use of Intelligent Transportation Systems (ITS) is a method of improving the conditions of communications, making it independent from the development of communications infrastructure. The attributes of neural networks are focused on solving the problems of optimisation, which involve the development of optimal strategies for traffic management. The proposed road traffic management system that uses ITS and neural networks can be applied in prediction of the conditions of communication…
A pre-processing technique based on the wavelet transform for linear autoassociators with applications to face recognition
1997
In order to improve the performance of a linear autoassociator (which is a neural network model), we explore the use of several preprocessing techniques. The gist of our approach is to store, in addition to the original pattern, one or several pre-processed (i.e. filtered) versions of the patterns to be stored in a neural network. First, we compare the performance of several pre-processing techniques (a plain vanilla version of the autoassociator as a control, a Sobel operator, a Canny-Deriche operator, and a multiscale Canny-Deriche operator) on an example of a pattern completion task using a noise degraded version of a face stored in an autoassociator. We found that the multiscale Canny-D…
Back to Pupillometry: How Cortical Network State Fluctuations Tracked by Pupil Dynamics Could Explain Neural Signal Variability in Human Cognitive Ne…
2017
Visual Abstract
Navigating the translational roadblock: Towards highly specific and effective all-optical interrogations of neural circuits
2020
AbstractTwo-photon (2-P) all-optical approaches combine in vivo 2-P calcium imaging and 2-P optogenetic modulations and have the potential to build a framework for network-based therapies, e.g. for rebalancing maladaptive activity patterns in preclinical models of neurological disorders. Here, our goal was to tailor these approaches for this purpose: Firstly, we combined in vivo juxtacellular recordings and GCaMP6f-based 2-P calcium imaging in layer II/III of mouse visual cortex to tune our detection algorithm towards a 100 % specific identification of AP-related calcium transients. False-positive-free detection was achieved at a sensitivity of approximately 73 %. To further increase specif…
A Computational Study on Temperature Variations in MRgFUS Treatments Using PRF Thermometry Techniques and Optical Probes
2021
Structural and metabolic imaging are fundamental for diagnosis, treatment and follow-up in oncology. Beyond the well-established diagnostic imaging applications, ultrasounds are currently emerging in the clinical practice as a noninvasive technology for therapy. Indeed, the sound waves can be used to increase the temperature inside the target solid tumors, leading to apoptosis or necrosis of neoplastic tissues. The Magnetic resonance-guided focused ultrasound surgery (MRgFUS) technology represents a valid application of this ultrasound property, mainly used in oncology and neurology. In this paper