| 41551. |
- Klevedal, Charlotta, et al.
(författare)
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Fetal-maternal outcomes and complications in pregnant women with polycystic ovary syndrome
- 2017
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Ingår i: Minerva Ginecologica. - Turin : Edizioni Minerva Medica. - 0026-4784 .- 1827-1650. ; 69:2, s. 141-149
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Earlier studies have shown that polycystic ovary syndrome (PCOS) is associated with cardiovascular disease as well as pregnancy complications. We examined whether women with PCOS have an increased risk of complications in pregnancy compared with healthy women, and if there are any correlations between complications and clinical/demographic variables before and/or in early pregnancy.METHODS: This retrospective cohort study comprised 37 women with PCOS and 126 healthy women whose birth was recorded at Sundsvall County Hospital, Sweden, from 2009 to 2014. Medical records were searched to identify pregnancy complications, maternal outcomes, and neonatal outcomes.RESULTS: Compared with healthy women, the women with PCOS were more likely to have a history of miscarriage (42.9% vs. 19.8% P=0.005) and undergo caesarean section (41.2% vs. 21.4%, P=0.019). They were also at increased risk of developing a complication (odds ratio 2.38, 95% CI: 1.05-5.38) or having multiple concurrent complications (odds ratio 8.27, 95% CI: 1.45-47.3). The rates of premature birth, birth weight and Apgar score at 5 min were similar between the two groups. The preconception serum testosterone concentration was positively correlated with the complication rate and negatively correlated with gestational age.CONCLUSIONS: We found that women with PCOS are at greater risk of complications during pregnancy than healthy women, consistent with the results of earlier studies. High testosterone concentrations could be an aggravating factor in the risk of complications. Therefore, women with PCOS may require more careful monitoring during pregnancy than healthy women.
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| 41552. |
- Klevjer, Thor A., et al.
(författare)
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In situ behaviour and acoustic properties of the deep living jellyfish Periphylla periphylla
- 2009
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Ingår i: Journal of Plankton Research. - : Oxford University Press (OUP). - 0142-7873 .- 1464-3774. ; 31:8, s. 793-803
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Tidskriftsartikel (refereegranskat)abstract
- The importance of jellyfish in marine systems is increasingly being recognized, and in some ecosystems, jellyfish may now be considered the top predator. We studied the behaviour of individuals of the deep-water schypozoan Periphylla periphylla in one such location, the Lurefjord, Norway. The study was performed using a combination of submersible acoustics (38 kHz), video and net methods, and the focus was on variation in behaviour and vertical distribution in relation to the diel cycle. A proportion of the population underwent synchronous vertical migrations, but P. periphylla were still recorded throughout the water column both day and night. The majority of individuals were swimming (vertically) at speeds < 2 cm s(-1) irrespective of the time of day. However, occasional vertical swimming events with speeds exceeding 10 cm s(-1) were recorded. Such events of elevated vertical speeds were of short duration, followed by subsequent periods of no vertical movements. Different size fractions appeared to have different patterns of vertical swimming activity, with smaller jellyfish swimming more continuously than the larger Periphylla. The echo strengths of the individual returns (target strength, TS) peaked at approximately -62 dB, and variability in TS for individuals was high, with the strongest echoes seen in deep water. The results show the feasibility of acoustic methods for studying the in situ behaviour and acoustic properties of these jellyfish, but also that acoustically weak jellyfish are only recorded close to the transducer or the acoustic axis, which will bias acoustic data on vertical size distribution and acoustic abundance estimates.
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| 41553. |
- Klewer, Laura, et al.
(författare)
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Light-Induced Dimerization Approaches to Control Cellular Processes
- 2019
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Ingår i: Chemistry - A European Journal. - : Wiley. - 0947-6539 .- 1521-3765. ; 25, s. 12452-12463
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Tidskriftsartikel (refereegranskat)abstract
- Light-inducible approaches provide a means to control biological systems with spatial and temporal resolution that is unmatched by traditional genetic perturbations. Recent developments of optogenetic and chemo-optogenetic systems for induced proximity in cells facilitate rapid and reversible manipulation of highly dynamic cellular processes and have become valuable tools in diverse biological applications. New expansions of the toolbox facilitate control of signal transduction, genome editing, "painting" patterns of active molecules onto cellular membranes, and light-induced cell cycle control. A combination of light- and chemically induced dimerization approaches have also seen interesting progress. Herein, an overview of optogenetic systems and emerging chemo-optogenetic systems is provided, and recent applications in tackling complex biological problems are discussed.
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| 41554. |
- Kleyko, Denis, 1990-, et al.
(författare)
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A Comprehensive Study of Complexity and Performance of Automatic Detection of Atrial Fibrillation : Classification of Long ECG Recordings Based on the PhysioNet Computing in Cardiology Challenge 2017
- 2020
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Ingår i: Biomedical Engineering & Physics Express. - : Institute of Physics Publishing (IOPP). - 2057-1976. ; 6:2
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Tidskriftsartikel (refereegranskat)abstract
- Objective: The 2017 PhysioNet/CinC Challenge focused on automatic classification of atrial fibrillation (AF) in short ECGs. This study aimed to evaluate the use of the data and results from the challenge for detection of AF in longer ECGs, taken from three other PhysioNet datasets.Approach: The used data-driven models were based on features extracted from ECG recordings, calculated according to three solutions from the challenge. A Random Forest classifier was trained with the data from the challenge. The performance was evaluated on all non-overlapping 30 s segments in all recordings from three MIT-BIH datasets. Fifty-six models were trained using different feature sets, both before and after applying three feature reduction techniques.Main Results: Based on rhythm annotations, the AF proportion was 0.00 in the MIT-BIH Normal Sinus Rhythm (N = 46083 segments), 0.10 in the MIT-BIH Arrhythmia (N = 2880), and 0.41 in the MIT-BIH Atrial Fibrillation (N = 28104) dataset. For the best performing model, the corresponding detected proportions of AF were 0.00, 0.11 and 0.36 using all features, and 0.01, 0.10 and 0.38 when using the 15 best performing features.Significance: The results obtained on the MIT-BIH datasets indicate that the training data and solutions from the 2017 Physionet/Cinc Challenge can be useful tools for developing robust AF detectors also in longer ECG recordings, even when using a low number of carefully selected features. The use of feature selection allows significantly reducing the number of features while preserving the classification performance, which can be important when building low-complexity AF classifiers on ECG devices with constrained computational and energy resources.
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| 41555. |
- Kleyko, Denis, 1990-, et al.
(författare)
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A Hyperdimensional Computing Framework for Analysis of Cardiorespiratory Synchronization during Paced Deep Breathing
- 2019
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Ingår i: IEEE Access. - : IEEE. - 2169-3536. ; 7, s. 34403-34415
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Tidskriftsartikel (refereegranskat)abstract
- Objective: Autonomic function during deep breathing (DB) is normally scored based on the assumption that the heart rate is synchronized with the breathing. We have observed individuals with subtle arrhythmias during DB where autonomic function cannot be evaluated. This study presents a novel method for analyzing cardiorespiratory synchronization: feature-based analysis of the similarity between heart rate and respiration using principles of hyperdimensional computing. Methods: Heart rate and respiration signals were modeled using Fourier series analysis. Three feature variables were derived and mapped to binary vectors in a high-dimensional space. Using both synthesized data and recordings from patients/healthy subjects, the similarity between the feature vectors was assessed using Hamming distance (high-dimensional space), Euclidean distance (original space), and with a coherence-based index. Methods were evaluated via classification of the similarity indices into three groups. Results: The distance-based methods achieved good separation of signals into classes with different degree of cardiorespiratory synchronization, also providing identification of patients with low cardiorespiratory synchronization but high values of conventional DB scores. Moreover, binary high-dimensional vectors allowed an additional analysis of the obtained Hamming distance. Conclusions: Feature-based similarity analysis using hyperdimensional computing is capable of identifying signals with low cardiorespiratory synchronization during DB due to arrhythmias. Vector-based similarity analysis could be applied to other types of feature variables than based on spectral analysis. Significance: The proposed methods for robustly assessing cardiorespiratory synchronization during DB facilitate the identification of individuals where the evaluation of autonomic function is problematic or even impossible, thus, increasing the correctness of the conventional DB scores.
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| 41556. |
- Kleyko, Denis, et al.
(författare)
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Density Encoding Enables Resource-Efficient Randomly Connected Neural Networks
- 2021
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Ingår i: IEEE Transactions on Neural Networks and Learning Systems. - : Institute of Electrical and Electronics Engineers Inc.. - 2162-237X .- 2162-2388. ; 32:8, s. 3777-3783
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Tidskriftsartikel (refereegranskat)abstract
- The deployment of machine learning algorithms on resource-constrained edge devices is an important challenge from both theoretical and applied points of view. In this brief, we focus on resource-efficient randomly connected neural networks known as random vector functional link (RVFL) networks since their simple design and extremely fast training time make them very attractive for solving many applied classification tasks. We propose to represent input features via the density-based encoding known in the area of stochastic computing and use the operations of binding and bundling from the area of hyperdimensional computing for obtaining the activations of the hidden neurons. Using a collection of 121 real-world data sets from the UCI machine learning repository, we empirically show that the proposed approach demonstrates higher average accuracy than the conventional RVFL. We also demonstrate that it is possible to represent the readout matrix using only integers in a limited range with minimal loss in the accuracy. In this case, the proposed approach operates only on small ${n}$ -bits integers, which results in a computationally efficient architecture. Finally, through hardware field-programmable gate array (FPGA) implementations, we show that such an approach consumes approximately 11 times less energy than that of the conventional RVFL.
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| 41557. |
- Kleyko, Denis, 1990-, et al.
(författare)
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Distributed Representation of n-gram Statistics for Boosting Self-organizing Maps with Hyperdimensional Computing
- 2019
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Ingår i: Perspectives of System Informatics. - Cham : Springer. ; , s. 64-79, s. 64-79
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Konferensbidrag (refereegranskat)abstract
- This paper presents an approach for substantial reduction of the training and operating phases of Self-Organizing Maps in tasks of 2-D projection of multi-dimensional symbolic data for natural language processing such as language classification, topic extraction, and ontology development. The conventional approach for this type of problem is to use n-gram statistics as a fixed size representation for input of Self-Organizing Maps. The performance bottleneck with n-gram statistics is that the size of representation and as a result the computation time of Self-Organizing Maps grows exponentially with the size of n-grams. The presented approach is based on distributed representations of structured data using principles of hyperdimensional computing. The experiments performed on the European languages recognition task demonstrate that Self-Organizing Maps trained with distributed representations require less computations than the conventional n-gram statistics while well preserving the overall performance of Self-Organizing Maps.
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| 41558. |
- Kleyko, Denis, 1990-, et al.
(författare)
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Integer Self-Organizing Maps for Digital Hardware
- 2019
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Ingår i: 2019 International Joint Conference on Neural Networks (IJCNN). - : IEEE. - 9781728119854
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Konferensbidrag (refereegranskat)abstract
- The Self-Organizing Map algorithm has been proven and demonstrated to be a useful paradigm for unsupervised machine learning of two-dimensional projections of multidimensional data. The tri-state Self-Organizing Maps have been proposed as an accelerated resource-efficient alternative to the Self-Organizing Maps for implementation on field-programmable gate array (FPGA) hardware. This paper presents a generalization of the tri-state Self-Organizing Maps. The proposed generalization, which we call integer Self-Organizing Maps, requires only integer operations for weight updates. The presented experiments demonstrated that the integer Self-Organizing Maps achieve better accuracy in a classification task when compared to the original tri-state Self-Organizing Maps.
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| 41559. |
- Kleyko, Denis, 1990-, et al.
(författare)
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Vector-Based Analysis of the Similarity Between Breathing and Heart Rate During Paced Deep Breathing
- 2018
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Ingår i: Computing in Cardiology 2018. - : IEEE.
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Konferensbidrag (refereegranskat)abstract
- The heart rate (HR) response to paced deep breathing (DB) is a common test of autonomic function, where the scoring is based on indices reflecting the overall heart rate variability (HRV), where high scores are considered as normal findings but can also reflect arrhythmias. This study presents a method based on hyperdimensional computing for assessment of the similarity between feature vectors derived from the HR and breathing signals. The proposed method was used to identify subjects where HR did not follow the paced breathing pattern in recordings from DB tests in 174 healthy subjects and 135 patients with cardiac autonomic neuropathy. Subjects were classified in 4 similarity classes, where the lowest similiarity class included 35 patients and 3 controls. In general, the autonomic function cannot be evaluated in subjects in the lowest similarity class if they also present with high HRV scores, since this combination is a strong indicator of the presence of arrhythmias. Thus, the proposed vector-based similarity analysis is one tool to identify subjects with high HRV but low cardiorespiratory synchronization during the DB test, which falsely can be interpreted as normal autonomic function.
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| 41560. |
- Kleyko, Denis, et al.
(författare)
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Vehicle Classification using Road Side Sensors and Feature-free Data Smashing Approach
- 2016
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Ingår i: 2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC). - Piscataway : IEEE. - 9781509018895 - 9781509018888 - 9781509018901 ; , s. 1988-1993
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Konferensbidrag (refereegranskat)abstract
- The main contribution of this paper is a study of the applicability of data smashing - a recently proposed data mining method - for vehicle classification according to the "Nordic system for intelligent classification of vehicles" standard, using measurements of road surface vibrations and magnetic field disturbances caused by passing vehicles. The main advantage of the studied classification approach is that it, in contrast to the most of traditional machine learning algorithms, does not require the extraction of features from raw signals. The proposed classification approach was evaluated on a large dataset consisting of signals from 3074 vehicles. Hence, a good estimate of the actual classification rate was obtained. The performance was compared to the previously reported results on the same problem for logistic regression. Our results show the potential trade-off between classification accuracy and classification method's development efforts could be achieved.
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