| 1. |
- Cutas, Daniela, 1978, et al.
(författare)
-
Legal imperialism in the regulation of stem cell research and therapy: the problem of extraterritorial jurisdiction
- 2010
-
Ingår i: Capps BJ & Campbell AV (eds.). CONTESTED CELLS: Global Perspectives on the Stem Cell Debate. - London : Imperial College Press. - 9781848164376 ; , s. 95-119
-
Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- Countries worldwide have very different national regulations on human embryonic stem (ES) cell research, informed by a range of ethical values. Some countries find reason to extend the applicability of their regulations on such research to its citizens when they visit other countries. Extraterritorial jurisdiction has recently been identified as a potential challenge towards global regulation of ES cell research. This chapter explores the implications and impact of extraterritorial jurisdiction and global regulation of ES cell research on researchers, clinicians and national health systems, and how this may affect patients. The authors argue that it would make ethical sense for ES cell restrictive countries to extend its regulations on ES cell research beyond its borders, because, if these countries really consider embryo destruction to be objectionable on the basis on the status of the embryo, then they ought to count it morally on par with murder (and thus have a moral imperative to protect embryos from the actions of its own citizens). However, doing so could lead to a legal situation that would result in substantial harm to central values in areas besides research, such as health care, the job market, basic freedom of movement, and strategic international finance and politics. Thus, it seems that restrictive extraterritorial jurisdiction in respect to ES cell research would be deeply problematic, given that the ethical permissibility of ES cell research is characterised by deep and wide disagreement.
|
|
| 2. |
- Robinson, Yohan, 1977, et al.
(författare)
-
AI och framtidens försvarsmedicin
- 2020
-
Rapport (övrigt vetenskapligt/konstnärligt)abstract
- Medicinskt legitimerad personal är, och kommer med stor sannolikhet fortsattatt vara, en knapp resurs inom Försvarsmaktens sjukvårdsorganisation. I denna rapport ges en översikt över pågående och planerade ansatser baserade påartificiell intelligens (AI) inom akutsjukvård med särskild tonvikt på omhändertagandet av traumapatienter, där lösningarna skulle kunna bidra till att Försvarsmakten kan bibehålla sin sjukvårdskapacitet i kritiska lägen. Rapporten är ett resultat av samarbetet mellan FM, FOI, FMV, FHS och KI, och vänder sig i första hand till Försvarsmaktens strategiska ledning.Användningen av AI-teknik i framtida beslutsstöd kan skapa nya möjligheter till avlastning av personal och resurseffektivisering. Tekniken ger möjligheter att i realtid samla in, bearbeta och analysera stora mängder blandadinformation om förbands hälsoläge och fysiska stridsvärde. Bedömning av skadade kan t.ex. göras av triagedrönare och den efterföljande evakueringen kanunderlättas av intelligenta autonoma plattformar. Införandet av AI-system ställer dock vårdgivaren inför svåra etiska och medikolegala överväganden.Försvarsmedicin har en central roll i Försvarsmaktens krigföringsförmåga och för samhällets uthållighet. För att nyttja hela AI-teknikens framfart till Försvarsmaktens nytta måste dess innebörd och konsekvens för försvarsmedicinen förstås. Därför rekommenderar denna studie att Försvarsmaktens framtida satsningar inom AI och autonomi inkluderar den försvarsmedicinska teknikutveckling som är beskriven i denna rapport.
|
|
| 3. |
- Henje, Catharina, 1960-, et al.
(författare)
-
Obstacles and risks in the traffic environment for users of powered wheelchairs in Sweden
- 2021
-
Ingår i: Accident Analysis and Prevention. - : Elsevier. - 0001-4575 .- 1879-2057. ; 159
-
Tidskriftsartikel (refereegranskat)abstract
- Objective: According to the European Union, fatal road accidents involving Vulnerable Road Users (VRUs) are equal in proportion to fatal car road accidents (46%). VRUs include individuals with mobility challenges such as the elderly and Powered Wheelchair (PWC) users. The aim of this interdisciplinary qualitative study was to identify obstacles and risks for PWC users by exploring their behaviour and experiences in traffic environments.Methods: Videos and in-depth interviews with 13 PWC users aged 20–66 were analysed for this study. The interviews and videos, which include real-life outdoor observations, originate from a qualitative study exploring experiences of PWC use on a daily basis in Sweden. Underlying causal factors to identified risks and obstacles were identified, based on human, vehicle (PWC) and environmental factors in accordance with the Haddon Matrix.Results: The results show significant potential for improvement within all three perspectives of the Haddon Matrix used in the analysis. Participants faced and dealt with various obstacles and risks in order to reach their destination. For example, this includes uneven surfaces, differences in ground levels, steep slopes, as well as interactions with other road users and the influence of weather conditions, resulting in PWC users constantly accommodating and coping with the shortcomings of the vehicle and the environment.Conclusions: There are still major challenges with regard to preventing obstacles and risks in the traffic environment for PWC users. To discern PWC users in traffic accident and injury data bases, a start would be to register type of aid used for persons involved in an accident. Furthermore, to emphasise PWC users’ role as VRUs, it may also be advantageous to describe them as drivers rather than users when navigating the traffic environment. Given the limited sample, further research covering more data from a broader perspective would be beneficial. By incorporating emerging knowledge of PWC users’ prerequisites and needs, and including them in research and traffic planning, the society will grow safer and more inclusive, and become better prepared for meeting future demands on accessibility from an aging population.
|
|
| 4. |
- Ali, Muhaddisa Barat, 1986, et al.
(författare)
-
A novel federated deep learning scheme for glioma and its subtype classification
- 2023
-
Ingår i: Frontiers in Neuroscience. - 1662-4548 .- 1662-453X. ; 17
-
Tidskriftsartikel (refereegranskat)abstract
- Background: Deep learning (DL) has shown promising results in molecular-based classification of glioma subtypes from MR images. DL requires a large number of training data for achieving good generalization performance. Since brain tumor datasets are usually small in size, combination of such datasets from different hospitals are needed. Data privacy issue from hospitals often poses a constraint on such a practice. Federated learning (FL) has gained much attention lately as it trains a central DL model without requiring data sharing from different hospitals. Method: We propose a novel 3D FL scheme for glioma and its molecular subtype classification. In the scheme, a slice-based DL classifier, EtFedDyn, is exploited which is an extension of FedDyn, with the key differences on using focal loss cost function to tackle severe class imbalances in the datasets, and on multi-stream network to exploit MRIs in different modalities. By combining EtFedDyn with domain mapping as the pre-processing and 3D scan-based post-processing, the proposed scheme makes 3D brain scan-based classification on datasets from different dataset owners. To examine whether the FL scheme could replace the central learning (CL) one, we then compare the classification performance between the proposed FL and the corresponding CL schemes. Furthermore, detailed empirical-based analysis were also conducted to exam the effect of using domain mapping, 3D scan-based post-processing, different cost functions and different FL schemes. Results: Experiments were done on two case studies: classification of glioma subtypes (IDH mutation and wild-type on TCGA and US datasets in case A) and glioma grades (high/low grade glioma HGG and LGG on MICCAI dataset in case B). The proposed FL scheme has obtained good performance on the test sets (85.46%, 75.56%) for IDH subtypes and (89.28%, 90.72%) for glioma LGG/HGG all averaged on five runs. Comparing with the corresponding CL scheme, the drop in test accuracy from the proposed FL scheme is small (−1.17%, −0.83%), indicating its good potential to replace the CL scheme. Furthermore, the empirically tests have shown that an increased classification test accuracy by applying: domain mapping (0.4%, 1.85%) in case A; focal loss function (1.66%, 3.25%) in case A and (1.19%, 1.85%) in case B; 3D post-processing (2.11%, 2.23%) in case A and (1.81%, 2.39%) in case B and EtFedDyn over FedAvg classifier (1.05%, 1.55%) in case A and (1.23%, 1.81%) in case B with fast convergence, which all contributed to the improvement of overall performance in the proposed FL scheme. Conclusion: The proposed FL scheme is shown to be effective in predicting glioma and its subtypes by using MR images from test sets, with great potential of replacing the conventional CL approaches for training deep networks. This could help hospitals to maintain their data privacy, while using a federated trained classifier with nearly similar performance as that from a centrally trained one. Further detailed experiments have shown that different parts in the proposed 3D FL scheme, such as domain mapping (make datasets more uniform) and post-processing (scan-based classification), are essential.
|
|
| 5. |
- Ge, Chenjie, 1991, et al.
(författare)
-
Enlarged Training Dataset by Pairwise GANs for Molecular-Based Brain Tumor Classification
- 2020
-
Ingår i: IEEE Access. - 2169-3536 .- 2169-3536. ; 8:1, s. 22560-22570
-
Tidskriftsartikel (refereegranskat)abstract
- This paper addresses issues of brain tumor subtype classification using Magnetic Resonance Images (MRIs) from different scanner modalities like T1 weighted, T1 weighted with contrast-enhanced, T2 weighted and FLAIR images. Currently most available glioma datasets are relatively moderate in size, and often accompanied with incomplete MRIs in different modalities. To tackle the commonly encountered problems of insufficiently large brain tumor datasets and incomplete modality of image for deep learning, we propose to add augmented brain MR images to enlarge the training dataset by employing a pairwise Generative Adversarial Network (GAN) model. The pairwise GAN is able to generate synthetic MRIs across different modalities. To achieve the patient-level diagnostic result, we propose a post-processing strategy to combine the slice-level glioma subtype classification results by majority voting. A two-stage course-to-fine training strategy is proposed to learn the glioma feature using GAN-augmented MRIs followed by real MRIs. To evaluate the effectiveness of the proposed scheme, experiments have been conducted on a brain tumor dataset for classifying glioma molecular subtypes: isocitrate dehydrogenase 1 (IDH1) mutation and IDH1 wild-type. Our results on the dataset have shown good performance (with test accuracy 88.82%). Comparisons with several state-of-the-art methods are also included.
|
|
| 6. |
- Ali, Muhaddisa Barat, 1986, et al.
(författare)
-
Multi-stream Convolutional Autoencoder and 2D Generative Adversarial Network for Glioma Classification
- 2019
-
Ingår i: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). - Cham : Springer International Publishing. - 1611-3349 .- 0302-9743. ; 11678 LNCS, s. 234-245
-
Konferensbidrag (refereegranskat)abstract
- Diagnosis and timely treatment play an important role in preventing brain tumor growth. Deep learning methods have gained much attention lately. Obtaining a large amount of annotated medical data remains a challenging issue. Furthermore, high dimensional features of brain images could lead to over-fitting. In this paper, we address the above issues. Firstly, we propose an architecture for Generative Adversarial Networks to generate good quality synthetic 2D MRIs from multi-modality MRIs (T1 contrast-enhanced, T2, FLAIR). Secondly, we propose a deep learning scheme based on 3-streams of Convolutional Autoencoders (CAEs) followed by sensor information fusion. The rational behind using CAEs is that it may improve glioma classification performance (as comparing with conventional CNNs), since CAEs offer noise robustness and also efficient feature reduction hence possibly reduce the over-fitting. A two-round training strategy is also applied by pre-training on GAN augmented synthetic MRIs followed by refined-training on original MRIs. Experiments on BraTS 2017 dataset have demonstrated the effectiveness of the proposed scheme (test accuracy 92.04%). Comparison with several exiting schemes has provided further support to the proposed scheme.
|
|
| 7. |
- Abtahi, Jahan, et al.
(författare)
-
Bisphosphonate coating might improve fixation of dental implants in the maxilla: A pilot study
- 2010
-
Ingår i: International Journal of Oral and Maxillofacial Surgery. - : Elsevier Science B.V., Amsterdam. - 0901-5027 .- 1399-0020. ; 39:7, s. 673-677
-
Tidskriftsartikel (refereegranskat)abstract
- This pilot study evaluates the clinical stability of bisphosphonate-coated dental implants placed using a two-stage surgical procedure in five patients. Each patient received seven regular Brånemark implants, one of which was coated with bisphosphonate in a fibrinogen matrix. The coated implant was inserted where the bone was expected to have the least favourable quality. The level of the marginal bone around each implant was measured by intraoral periapical radiographs and implant stability was recorded using resonance frequency measurements. Frequency values (ISQ) were obtained peroperatively before flap closure and after 6 months at abutment connection. At abutment connection the bisphosphonate-coated implants were removed en bloc in two patients for histological examination. An animal experiment had previously confirmed that gamma-sterilization did not reduce bioactivity of the bisphosphonate coating. In each patient, the bisphosphonate-coated implant showed the largest improvement in ISQ level of all implants. Their values at the start tended to be lower, and the absolute value at 6 months did not differ. No complications occurred with the coated implants. Histology showed no abnormalities. Improvement in ISQ values was an expected effect of the bisphosphonate coating, but could be due to the choice of insertion site. This finding warrants a randomized, blinded study.
|
|
| 8. |
- Ge, Chenjie, 1991, et al.
(författare)
-
Cross-Modality Augmentation of Brain Mr Images Using a Novel Pairwise Generative Adversarial Network for Enhanced Glioma Classification
- 2019
-
Ingår i: Proceedings - International Conference on Image Processing, ICIP. - 1522-4880.
-
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).
|
|
| 9. |
- Farahmand, Dan, et al.
(författare)
-
Intracranial pressure in hydrocephalus: impact of shunt adjustments and body positions
- 2015
-
Ingår i: Journal of Neurology Neurosurgery and Psychiatry. - : BMJ. - 0022-3050 .- 1468-330X. ; 86:2, s. 222-228
-
Tidskriftsartikel (refereegranskat)abstract
- Background The association between intracranial pressure (ICP) and different shunt valve opening pressures in relation to body positions is fundamental for understanding the physiological function of the shunt. Objective To analyse the ICP and ICP wave amplitude (AMP) at different shunt settings and body positions in patients with hydrocephalus. Methods In this prospective study 15 patients with communicating hydrocephalus were implanted with a ligated adjustable ventriculoperitoneal shunt. They also received a portable intraparenchymatous ICP-monitoring device. Postoperative ICP and AMP were recorded with the patients in three different body positions (supine, sitting and walking) and with the shunt ligated and open at high, medium and low valve settings. In each patient 12 10 min segments were coded, blinded and analysed for mean ICP and mean AMP using an automated computer algorithm. Results Mean ICP and mean AMP were lower at all three valve settings compared with the ligated shunt state (p<0.001). Overall, when compared with the supine position, mean ICP was 11.5 +/- 1.1 (mean +/- SD) mm Hg lower when sitting and 10.5 +/- 1.1 mm Hg lower when walking (p<0.001). Mean ICP was overall 1.1 mm Hg higher (p=0.042) when walking compared with sitting. The maximal adjustability difference (highest vs lowest valve setting) was 4.4 mm Hg. Conclusions Changing from a supine to an upright position reduced ICP while AMP only increased at trend level. Lowering of the shunt valve opening pressure decreased ICP and AMP but the difference in mean ICP in vivo between the highest and lowest opening pressures was less than half that previously observed in vitro.
|
|
| 10. |
- Haj-Hosseini, Neda, 1980-, et al.
(författare)
-
Early Detection of Oral Potentially Malignant Disorders: A Review on Prospective Screening Methods with Regard to Global Challenges
- 2024
-
Ingår i: Journal of Maxillofacial & Oral Surgery. - New Delhi, India : Springer Science and Business Media LLC. - 0972-8279 .- 0974-942X. ; 23:1, s. 23-32
-
Tidskriftsartikel (refereegranskat)abstract
- Oral cancer is a cancer type that is widely prevalent in low-and middle-income countries with a high mortality rate, and poor quality of life for patients after treatment. Early treatment of cancer increases patient survival, improves quality of life and results in less morbidity and a better prognosis. To reach this goal, early detection of malignancies using technologies that can be used in remote and low resource areas is desirable. Such technologies should be affordable, accurate, and easy to use and interpret. This review surveys different technologies that have the potentials of implementation in primary health and general dental practice, considering global perspectives and with a focus on the population in India, where oral cancer is highly prevalent. The technologies reviewed include both sample-based methods, such as saliva and blood analysis and brush biopsy, and more direct screening of the oral cavity including fluorescence, Raman techniques, and optical coherence tomography. Digitalisation, followed by automated artificial intelligence based analysis, are key elements in facilitating wide access to these technologies, to non-specialist personnel and in rural areas, increasing quality and objectivity of the analysis while simultaneously reducing the labour and need for highly trained specialists.
|
|
