Search results for "Neural Networks"
showing 10 items of 599 documents
Is neural network better than logistic regression in death prediction in patients after ST-segment elevation myocardial infarction?
2021
Background: There is a need to develop patient classification methods to adjust post-discharge care, improving survival after ST-segment elevation myocardial infarction (STEMI). Aims: The study aimed to determine whether a neural network (NN) is better than logistic regression (LR) in mortality prediction in STEMI patients. Material and methods: The study included patients from the Polish Registry of Acute Coronary Syndromes (PL-ACS). Patients with the first anterior STEMI treated with the primary percutaneous coronary intervention (pPCI) of the left anterior descending (LAD) artery between 2009 and 2015 and discharged alive were included in the study. Patients were randomly divided into th…
Predicting survival after transarterial chemoembolization for hepatocellular carcinoma using a neural network: A Pilot Study.
2019
BACKGROUND AND AIMS Deciding when to repeat and when to stop transarterial chemoembolization (TACE) in patients with hepatocellular carcinoma (HCC) can be difficult even for experienced investigators. Our aim was to develop a survival prediction model for such patients undergoing TACE using novel machine learning algorithms and to compare it to conventional prediction scores, ART, ABCR and SNACOR. METHODS For this retrospective analysis, 282 patients who underwent TACE for HCC at our tertiary referral centre between January 2005 and December 2017 were included in the final analysis. We built an artificial neural network (ANN) including all parameters used by the aforementioned risk scores a…
Enhanced prediction of hemoglobin concentration in a very large cohort of hemodialysis patients by means of deep recurrent neural networks.
2019
Erythropoiesis Stimulating Agents (ESAs) have become a standard anemia management tool for End Stage Renal Disease (ESRD) patients. However, dose optimization constitutes an extremely challenging task due to huge inter and intra-patient variability in the responses to ESA administration. Current data-based approaches to anemia control focus on learning accurate hemoglobin prediction models, which can be later utilized for testing competing treatment choices and choosing the optimal one. These methods, despite being proven effective in practice, present several shortcomings which this paper intends to tackle. Namely, they are limited to a small cohort of patients and, even then, they fail to…
A CAD system for nodule detection in low-dose lung CTs based on region growing and a new active contour model
2007
A computer-aided detection (CAD) system for the selection of lung nodules in computer tomography (CT) images is presented. The system is based on region growing (RG) algorithms and a new active contour model (ACM), implementing a local convex hull, able to draw the correct contour of the lung parenchyma and to include the pleural nodules. The CAD consists of three steps: (1) the lung parenchymal volume is segmented by means of a RG algorithm; the pleural nodules are included through the new ACM technique; (2) a RG algorithm is iteratively applied to the previously segmented volume in order to detect the candidate nodules; (3) a double-threshold cut and a neural network are applied to reduce…
Dropout from exercise randomized controlled trials among people with depression: A meta-analysis and meta regression
2015
Abstract Objective Exercise has established efficacy in improving depressive symptoms. Dropouts from randomized controlled trials (RCT’s) pose a threat to the validity of this evidence base, with dropout rates varying across studies. We conducted a systematic review and meta-analysis to investigate the prevalence and predictors of dropout rates among adults with depression participating in exercise RCT’s. Method Three authors identified RCT’s from a recent Cochrane review and conducted updated searches of major electronic databases from 01/2013 to 08/2015. We included RCT’s of exercise interventions in people with depression (including major depressive disorder (MDD) and depressive symptoms…
Recognition of rapid-eye-movement sleep from single-channel EEG data by artificial neural networks: a study in depressive patients with and without a…
1996
An automatic procedure for the online recognition of REM sleep appears to be a necessary tool for selective REM sleep deprivation in depressive patients. To develop such a procedure we applied an artificial neural network to preprocessed single-channel EEG activity. EOG and EMG information was purposely not provided as input to the network. A generalized back-propagation algorithm was used for computer simulation. The sleep profile scored manually according to Rechtschaffen and Kales served as the desired output during the training period and as standard for the judgement of the network output during working mode. Polysomnographic recordings from 5 healthy subjects were pooled to train the …
Influence of Attitudes towards Change and Self-directness on Dropout in Eating Disorders: A 2-Year Follow-up Study
2012
Objective This study examined dropout-related factors at the Outpatient Eating Disorders Treatment Programme. Method One hundred ninety-six eating disorders patients following DSM-IV diagnostic criteria that consecutively commenced treatment were recruited and followed up for a 2-year period. A total of 151 patients completed the whole assessment with a set of questionnaires evaluating eating and general psychopathology. The Attitudes towards Change in Eating Disorders questionnaire was used, and personality was evaluated using the Temperament and Character Inventory. During the follow-up period, patients were re-assessed. Two years later, 102 patients continued on treatment. Results Scores…
Use of neural networks for dosage individualisation of erythropoietin in patients with secondary anemia to chronic renal failure.
2003
The external administration of recombinant human erythropoietin is the chosen treatment for those patients with secondary anemia due to chronic renal failure undergoing periodic hemodialysis. The goal is to carry out an individualised prediction of the erythropoietin dosage to be administered. It is justified because of the high cost of this medication, its secondary effects and the phenomenon of potential resistance which some individuals suffer. One hundred and ten patients were included in this study and several factors were collected in order to develop the neural models. Since the results obtained were excellent, an easy-to-use decision-aid computer application was implemented.
A Navigation and Augmented Reality System for Visually Impaired People
2021
In recent years, we have assisted with an impressive advance in augmented reality systems and computer vision algorithms, based on image processing and artificial intelligence. Thanks to these technologies, mainstream smartphones are able to estimate their own motion in 3D space with high accuracy. In this paper, we exploit such technologies to support the autonomous mobility of people with visual disabilities, identifying pre-defined virtual paths and providing context information, reducing the distance between the digital and real worlds. In particular, we present ARIANNA+, an extension of ARIANNA, a system explicitly designed for visually impaired people for indoor and outdoor localizati…
Hyper-flexible Convolutional Neural Networks based on Generalized Lehmer and Power Means
2022
Convolutional Neural Network is one of the famous members of the deep learning family of neural network architectures, which is used for many purposes, including image classification. In spite of the wide adoption, such networks are known to be highly tuned to the training data (samples representing a particular problem), and they are poorly reusable to address new problems. One way to change this would be, in addition to trainable weights, to apply trainable parameters of the mathematical functions, which simulate various neural computations within such networks. In this way, we may distinguish between the narrowly focused task-specific parameters (weights) and more generic capability-spec…