| 41. |
- Culverhouse, R. C., et al.
(författare)
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Collaborative meta-analysis finds no evidence of a strong interaction between stress and 5-HTTLPR genotype contributing to the development of depression
- 2018
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Ingår i: Molecular Psychiatry. - : Springer Science and Business Media LLC. - 1359-4184 .- 1476-5578. ; 23:1, s. 133-142
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Tidskriftsartikel (refereegranskat)abstract
- The hypothesis that the S allele of the 5-HTTLPR serotonin transporter promoter region is associated with increased risk of depression, but only in individuals exposed to stressful situations, has generated much interest, research and controversy since first proposed in 2003. Multiple meta-analyses combining results from heterogeneous analyses have not settled the issue. To determine the magnitude of the interaction and the conditions under which it might be observed, we performed new analyses on 31 data sets containing 38 802 European ancestry subjects genotyped for 5-HTTLPR and assessed for depression and childhood maltreatment or other stressful life events, and meta-analysed the results. Analyses targeted two stressors (narrow, broad) and two depression outcomes (current, lifetime). All groups that published on this topic prior to the initiation of our study and met the assessment and sample size criteria were invited to participate. Additional groups, identified by consortium members or self-identified in response to our protocol (published prior to the start of analysis) with qualifying unpublished data, were also invited to participate. A uniform data analysis script implementing the protocol was executed by each of the consortium members. Our findings do not support the interaction hypothesis. We found no subgroups or variable definitions for which an interaction between stress and 5-HTTLPR genotype was statistically significant. In contrast, our findings for the main effects of life stressors (strong risk factor) and 5-HTTLPR genotype (no impact on risk) are strikingly consistent across our contributing studies, the original study reporting the interaction and subsequent meta-analyses. Our conclusion is that if an interaction exists in which the S allele of 5-HTTLPR increases risk of depression only in stressed individuals, then it is not broadly generalisable, but must be of modest effect size and only observable in limited situations.
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| 42. |
- Munthe, Christian, 1962
(författare)
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The Return of Lombroso? Ethical and Philosophical Aspects of (Visions of) Forensic Screening
- 2013
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Ingår i: 33rd International Congress of Law and Mental Health, Amsterdam, July 14-19, 2013.
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Konferensbidrag (refereegranskat)abstract
- Italian nineteenth century criminologist Cesare Lombroso is notorious for his seminal ideas about criminality and anti-social behaviour resulting from physiological anomalies that should be detected by society and used for forensic preventive purposes. After an extended period of disrepute following World War II, similar ideas have been resurrected in psychiatry, genetics, neurology and criminology in the past decade or two. In particular, there is a growing focus on early detection and application of preventive measures. This development actualizes a complex web of ethics and policy issues having to do with the well-known fact that screening and prevention in the health area are far from ethically clear-cut activities and actualize vivid prospects of doing extensive harm to individuals as well as society. Also, taken to its extreme, it actualizes the idea of using prenatal or preimplantation testing to preselect against children with a predisposition for criminal or antisocial behaviour. In the forensic case, such screening-prevention strategies will connect further to a complicated issue about the proper use of risk-assessment models for societal decision-making for precautionary purposes. Based on former work in all of these areas, this presentation will outline and analyze the basic issue of the defensibility of activities of this sort, with the perspective of forestalling unintentional harm to individuals and society.
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| 43. |
- Ge, Chenjie, 1991, et al.
(författare)
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Cross-Modality Augmentation of Brain Mr Images Using a Novel Pairwise Generative Adversarial Network for Enhanced Glioma Classification
- 2019
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Ingår i: Proceedings - International Conference on Image Processing, ICIP. - 1522-4880.
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Konferensbidrag (refereegranskat)abstract
- © 2019 IEEE. Brain Magnetic Resonance Images (MRIs) are commonly used for tumor diagnosis. Machine learning for brain tumor characterization often uses MRIs from many modalities (e.g., T1-MRI, Enhanced-T1-MRI, T2-MRI and FLAIR). This paper tackles two issues that may impact brain tumor characterization performance from deep learning: insufficiently large training dataset, and incomplete collection of MRIs from different modalities. We propose a novel pairwise generative adversarial network (GAN) architecture for generating synthetic brain MRIs in missing modalities by using existing MRIs in other modalities. By improving the training dataset, we aim to mitigate the overfitting and improve the deep learning performance. Main contributions of the paper include: (a) propose a pairwise generative adversarial network (GAN) for brain image augmentation via cross-modality image generation; (b) propose a training strategy to enhance the glioma classification performance, where GAN-augmented images are used for pre-training, followed by refined-training using real brain MRIs; (c) demonstrate the proposed method through tests and comparisons of glioma classifiers that are trained from mixing real and GAN synthetic data, as well as from real data only. Experiments were conducted on an open TCGA dataset, containing 167 subjects for classifying IDH genotypes (mutation or wild-type). Test results from two experimental settings have both provided supports to the proposed method, where glioma classification performance has consistently improved by using mixed real and augmented data (test accuracy 81.03%, with 2.57% improvement).
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| 44. |
- Javeed, Ashir, 1989-, et al.
(författare)
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Decision Support System for Predicting Mortality in Cardiac Patients Based on Machine Learning
- 2023
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Ingår i: Applied Sciences. - : MDPI. - 2076-3417. ; 13:8
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Tidskriftsartikel (refereegranskat)abstract
- Researchers have proposed several automated diagnostic systems based on machine learning and data mining techniques to predict heart failure. However, researchers have not paid close attention to predicting cardiac patient mortality. We developed a clinical decision support system for predicting mortality in cardiac patients to address this problem. The dataset collected for the experimental purposes of the proposed model consisted of 55 features with a total of 368 samples. We found that the classes in the dataset were highly imbalanced. To avoid the problem of bias in the machine learning model, we used the synthetic minority oversampling technique (SMOTE). After balancing the classes in the dataset, the newly proposed system employed a (Formula presented.) statistical model to rank the features from the dataset. The highest-ranked features were fed into an optimized random forest (RF) model for classification. The hyperparameters of the RF classifier were optimized using a grid search algorithm. The performance of the newly proposed model ((Formula presented.) _RF) was validated using several evaluation measures, including accuracy, sensitivity, specificity, F1 score, and a receiver operating characteristic (ROC) curve. With only 10 features from the dataset, the proposed model (Formula presented.) _RF achieved the highest accuracy of 94.59%. The proposed model (Formula presented.) _RF improved the performance of the standard RF model by 5.5%. Moreover, the proposed model (Formula presented.) _RF was compared with other state-of-the-art machine learning models. The experimental results show that the newly proposed decision support system outperforms the other machine learning systems using the same feature selection module ((Formula presented.)).
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| 45. |
- Åkerman, Linda, 1983-
(författare)
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Aspects of the Pre-Diabetic Period in Type 1 Diabetes
- 2016
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Type 1 diabetes (T1D) is an autoimmune disease characterized by insulin deficiency, due to immune-mediated destruction of beta cells. Current knowledge regarding the period preceding disease onset comes, to a large extent, from studying risk cohorts based on relatives of T1D-patients, as they have an increased disease risk. Among T1D patients in general, however, few have the disease in their immediate family. It is therefore important to study risk cohorts from the general population as well. An ongoing autoimmune reaction can often be seen in the blood long before disease onset, by detection of autoantibodies directed towards beta cell antigens. By autoantibody screening among participants in the ABIS (All Babies in the South-east of Sweden) cohort, we could identify a group of children from the general population with increased risk for T1D, positive for multiple autoantibodies. They were enrolled in a 2-year prospective follow-up aiming to characterize the prediabetic period and to identify factors indicative of progression/non-progression to T1D. We assessed glucose homeostasis and autoantibody titers over time, and searched for risk-biomarkers by analyzing the expression of immune-related genes (Th1-Th2-Th3) in peripheral blood mononuclear cells (PBMC) from these children, in comparison to healthy children and newly diagnosed T1D patients. In the same groups we also compared serum micro RNA (miRNA) profiles, knowing that miRNA molecules have desirable biomarker properties. We found that two specific autoantibodies, IA2A and ZnT8A, were detected at higher concentrations in risk-individuals who progressed to overt T1D during or after the follow-up period, compared to those who still have not. We also observed disturbed glucose homeostasis long before onset in the progressors, but it was seen among those who remain symptom free as well. Further, we found support for the possible role of insulin resistance as an accelerator of the disease process. For gene expression and serum miRNA, few differences were observed between risk-individuals and healthy children overall. However, for PBMC gene expression and serum miRNA both, there were associations to beta cell function and glucose homeostasis, and for miRNA also to islet autoantibodies. Although specific profiles for prediction of disease onset or identification of risk-individuals could not be found, these results are interesting and deserve to be evaluated further. As part of another sub-study within ABIS, the effects of physical activity on glucose homeostasis were assessed in healthy schoolchildren. The level of physical activity, measured by pedometers, was related to insulin resistance and beta cell-stress, and decreased physical activity was associated with increased insulin resistance and load on the insulin-producing beta cells, already at school-age.
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| 46. |
- Pontén, Eva, et al.
(författare)
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Higher amount of MyHC IIX in a wrist flexor in tetraplegic compared to hemiplegic cerebral palsy
- 2008
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Ingår i: Journal of the Neurological Sciences. - : Elsevier. - 0022-510X .- 1878-5883. ; 266:1-2, s. 51-56
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Spastic cerebral palsy can be divided into diagnostic groups by the relative severity of the arm impairment. This study investigates if hemiplegic, tetraplegic or diplegic cerebral palsy (CP) results in different patterns of myosin heavy chain (MyHC) expression in the flexor carpi ulnaris muscle from 17 young patients with CP. Using enzyme-immunohistochemistry and gel electrophoresis techniques we found a higher percentage of fibers expressing fast MyHC IIx (52%) in tetraplegic CP compared to hemiplegic patients (32%), (p < 0.05). Tetraplegic CP also resulted in a lower amount of fibers expressing slow MyHC I (18%) compared to hemiplegic CP (40%), (p < 0.005). The proportion of muscle fibers containing fetal MyHC was higher in tetraplegic CP compared to other groups, (p < 0.005). Taken together theses results indicate that tetraplegic CP is associated with a shift from slow to fast myosins and that regenerative events are more prominent in tetraplegic CP compared with milder brain damage.
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| 47. |
- de Dios, Eddie, et al.
(författare)
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Introduction to Deep Learning in Clinical Neuroscience
- 2022
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Ingår i: Acta Neurochirurgica, Supplement. - Cham : Springer International Publishing. - 2197-8395 .- 0065-1419. ; , s. 79-89
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- The use of deep learning (DL) is rapidly increasing in clinical neuroscience. The term denotes models with multiple sequential layers of learning algorithms, architecturally similar to neural networks of the brain. We provide examples of DL in analyzing MRI data and discuss potential applications and methodological caveats. Important aspects are data pre-processing, volumetric segmentation, and specific task-performing DL methods, such as CNNs and AEs. Additionally, GAN-expansion and domain mapping are useful DL techniques for generating artificial data and combining several smaller datasets. We present results of DL-based segmentation and accuracy in predicting glioma subtypes based on MRI features. Dice scores range from 0.77 to 0.89. In mixed glioma cohorts, IDH mutation can be predicted with a sensitivity of 0.98 and specificity of 0.97. Results in test cohorts have shown improvements of 5–7% in accuracy, following GAN-expansion of data and domain mapping of smaller datasets. The provided DL examples are promising, although not yet in clinical practice. DL has demonstrated usefulness in data augmentation and for overcoming data variability. DL methods should be further studied, developed, and validated for broader clinical use. Ultimately, DL models can serve as effective decision support systems, and are especially well-suited for time-consuming, detail-focused, and data-ample tasks.
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| 48. |
- Pourhamidi, Kaveh, et al.
(författare)
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Evaluation of clinical tools and their diagnostic use in distal symmetric polyneuropathy
- 2014
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Ingår i: Primary care diabetes. - : Elsevier. - 1878-0210 .- 1751-9918. ; 8:1, s. 77-84
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Tidskriftsartikel (refereegranskat)abstract
- AIMS: To compare the diagnostic usefulness of tuning fork, monofilament, biothesiometer and skin biopsies in peripheral neuropathy in individuals with varying glucose metabolism.METHODS: Normoglycaemic, impaired glucose tolerance (IGT) and type 2 diabetes (T2DM) individuals were recruited. Nerve conduction studies (NCS) and thermal threshold tests were performed. Vibrotactile sense was tested with a biothesiometer and a 128-Hz tuning fork. Touch/pressure perception was examined with a 10-g monofilament. Skin biopsies were performed and intraepidermal nerve fibres were quantified. Distal symmetric polyneuropathy (DSPN) was defined as neuropathy disability score ≥2 and abnormal NCS. Thermal threshold tests were used to define small nerve fibre neuropathy (sDSPN) in cases where NCS (large nerve fibres) were normal.RESULTS: The prevalence of DSPN and sDSPN in the whole group (n=119) was 18% and 23%, respectively. For the biothesiometer, a cut-off of ≥24.5V had a sensitivity of 82% and specificity of 70% (AUC=0.81, 95% CI 0.71-0.91) when evaluating DSPN. An intraepidermal nerve fibre density cut-off of ≤3.39fibres/mm showed a sensitivity of 74% and specificity of 70% in the detection of sDSPN, whereas the sensitivity of the tuning fork and the biothesiometer were relatively low, 46% and 67%, respectively. When combining skin biopsies with the tuning fork, 10 more sDSPN cases were identified. Adding skin biopsy to the combination of the tuning fork and biothesiometer increased the sensitivity of finding sDSPN cases, but not DSPN, from 81% to 93%.CONCLUSION: Using a biothesiometer in clinical routine might be a sensitive method to detect large nerve fibre dysfunction in the lower extremity, whereas skin biopsies in combination with methods measuring vibrotactile sense could increase the diagnostic sensitivity of detecting peripheral neuropathy at an early stage.
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| 49. |
- Slijper, Angelique, et al.
(författare)
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Computer game-based upper extremity training in the home environment in stroke persons : a single subject design
- 2014
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Ingår i: Journal of NeuroEngineering and Rehabilitation. - : Biomed Central. - 1743-0003. ; 11:1
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: The objective of the present study was to assess whether computer game-based training in the home setting in the late phase after stroke could improve upper extremity motor function.METHODS: Twelve subjects with prior stroke were recruited; 11 completed the study.DESIGN: The study had a single subject design; there was a baseline test (A1), a during intervention test (B) once a week, a post-test (A2) measured directly after the treatment phase, plus a follow-up (C) 16-18 weeks after the treatment phase. Information on motor function (Fugl-Meyer), grip force (GrippitR) and arm function in activity (ARAT, ABILHAND) was gathered at A1, A2 and C. During B, only Fugl-Meyer and ARAT were measured. The intervention comprised five weeks of game-based computer training in the home environment. All games were designed to be controlled by either the affected arm alone or by both arms. Conventional formulae were used to calculate the mean, median and standard deviations. Wilcoxon's signed rank test was used for tests of dependent samples. Continuous data were analyzed by methods for repeated measures and ordinal data were analyzed by methods for ordered multinomial data using cumulative logistic models. A p-value of < 0.05 was considered statistically significant.RESULTS: Six females and five males, participated in the study with an average age of 58 years (range 26-66). FMA-UE A-D (motor function), ARAT, the maximal grip force and the mean grip force on the affected side show significant improvements at post-test and follow-up compared to baseline. No significant correlation was found between the amount of game time and changes in the outcomes investigated in this study.CONCLUSION: The results indicate that computer game-based training could be a promising approach to improve upper extremity function in the late phase after stroke, since in this study, changes were achieved in motor function and activity capacity.
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| 50. |
- Religa, D., et al.
(författare)
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SveDem, the Swedish Dementia Registry - A tool for improving the quality of diagnostics, treatment and care of dementia patients in clinical practice
- 2015
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Ingår i: PLoS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 10:2
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Tidskriftsartikel (refereegranskat)abstract
- Background: The Swedish Dementia Registry (SveDem) was developed with the aim to improve the quality of diagnostic work-up, treatment and care of patients with dementia disorders in Sweden. Methods: SveDem is an internet based quality registry where several indicators can be followed over time. It includes information about the diagnostic work-up, medical treatment and community support (www.svedem.se). The patients are diagnosed and followed-up yearly in specialist units, primary care centres or in nursing homes. Results: The database was initiated in May 2007 and covers almost all of Sweden. There were 28 722 patients registered with a mean age of 79.3 years during 2007-2012. Each participating unit obtains continuous online statistics from its own registrations and they can be compared with regional and national data. A report from SveDem is published yearly to inform medical and care professionals as well as political and administrative decision-makers about the current quality of diagnostics, treatment and care of patients with dementia disorders in Sweden. Conclusion: SveDem provides knowledge about current dementia care in Sweden and serves as a framework for ensuring the quality of diagnostics, treatment and care across the country. It also reflects changes in quality dementia care over time. Data from SveDem can be used to further develop the national guidelines for dementia and to generate new research hypotheses.
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