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| 2. |
- Liu, Yuanhua, 1971, et al.
(författare)
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Considering the importance of user profiles in interface design
- 2009
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Ingår i: User Interfaces. ; , s. 23-
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- User profile is a popular term widely employed during product design processes by industrial companies. Such a profile is normally intended to represent real users of a product. The ultimate purpose of a user profile is actually to help designers to recognize or learn about the real user by presenting them with a description of a real user’s attributes, for instance; the user’s gender, age, educational level, attitude, technical needs and skill level. The aim of this chapter is to provide information on the current knowledge and research about user profile issues, as well as to emphasize the importance of considering these issues in interface design. In this chapter, we mainly focus on how users’ difference in expertise affects their performance or activity in various interaction contexts. Considering the complex interaction situations in practice, novice and expert users’ interactions with medical user interfaces of different technical complexity will be analyzed as examples: one focuses on novice and expert users’ difference when interacting with simple medical interfaces, and the other focuses on differences when interacting with complex medical interfaces. Four issues will be analyzed and discussed: (1) how novice and expert users differ in terms of performance during the interaction; (2) how novice and expert users differ in the perspective of cognitive mental models during the interaction; (3) how novice and expert users should be defined in practice; and (4) what are the main differences between novice and expert users’ implications for interface design. Besides describing the effect of users’ expertise difference during the interface design process, we will also pinpoint some potential problems for the research on interface design, as well as some future challenges that academic researchers and industrial engineers should face in practice.
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| 3. |
- Pepic, I., et al.
(författare)
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Early detection of sepsis using artificial intelligence : a scoping review protocol
- 2021
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Ingår i: Systematic Reviews. - : Springer Nature. - 2046-4053. ; 10:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection. To decrease the high case fatality rates and morbidity for sepsis and septic shock, there is a need to increase the accuracy of early detection of suspected sepsis in prehospital and emergency department settings. This may be achieved by developing risk prediction decision support systems based on artificial intelligence.Methods: The overall aim of this scoping review is to summarize the literature on existing methods for early detection of sepsis using artificial intelligence. The review will be performed using the framework formulated by Arksey and O’Malley and further developed by Levac and colleagues. To identify primary studies and reviews that are suitable to answer our research questions, a comprehensive literature collection will be compiled by searching several sources. Constrictions regarding time and language will have to be implemented. Therefore, only studies published between 1 January 1990 and 31 December 2020 will be taken into consideration, and foreign language publications will not be considered, i.e., only papers with full text in English will be included. Databases/web search engines that will be used are PubMed, Web of Science Platform, Scopus, IEEE Xplore, Google Scholar, Cochrane Library, and ACM Digital Library. Furthermore, clinical studies that have completed patient recruitment and reported results found in the database ClinicalTrials.gov will be considered. The term artificial intelligence is viewed broadly, and a wide range of machine learning and mathematical models suitable as base for decision support will be evaluated. Two members of the team will test the framework on a sample of included studies to ensure that the coding framework is suitable and can be consistently applied. Analysis of collected data will provide a descriptive summary and thematic analysis. The reported results will convey knowledge about the state of current research and innovation for using artificial intelligence to detect sepsis in early phases of the medical care chain.Ethics and dissemination: The methodology used here is based on the use of publicly available information and does not need ethical approval. It aims at aiding further research towards digital solutions for disease detection and health innovation. Results will be extracted into a review report for submission to a peer-reviewed scientific journal. Results will be shared with relevant local and national authorities and disseminated in additional appropriate formats such as conferences, lectures, and press releases.
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| 4. |
- Ali, Muhaddisa Barat, 1986, et al.
(författare)
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A novel federated deep learning scheme for glioma and its subtype classification
- 2023
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Ingår i: Frontiers in Neuroscience. - 1662-4548 .- 1662-453X. ; 17
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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.
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| 5. |
- Jonsdottir, Ingibjörg H, 1966, et al.
(författare)
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A pre/post analysis of the impact of the COVID-19 pandemic on the psychosocial work environment and recovery among healthcare workers in a large university hospital in Sweden
- 2021
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Ingår i: Journal of Public Health Research. - : SAGE Publications. - 2279-9028 .- 2279-9036. ; 10:4
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Tidskriftsartikel (refereegranskat)abstract
- Background: The impact of the COVID-19 pandemic on workload, mental health, and well-being of healthcare workers, and particularly those on the front-line, has received considerable attention. Design and methods: We surveyed hospital employees about their working environment during the pandemic and identified departments which were negatively affected in comparison to the pre-pandemic situation, as well as factors contributing to this. Setting and participants We surveyed all hospital employees at Sahlgrenska University Hospital, Sweden in September 2020 and compared results across departments and to the results of a large employee survey from October 2019. Results: The overall impact of the pandemic on perceived working conditions and possibility for recovery differed among departments. During the pandemic, healthcare workers working with COVID-19 patients reported poorer working environments than other employees. Factors significantly related to perception of work environment and recovery during the pandemic included worries of being infected, departmental transfer, and having insufficient access to personal protective equipment. Men reported better working conditions than women in all, but one item and higher age was related to better perceived working environment. Conclusions: Our results indicate that the pandemic differentially affects hospital departments and underscores the multifactorial nature of this topic. Contributing factors to poor perceived working environment could be addressed at times of high workload, such as during the pandemic, including providing appropriate support to managers, ensuring possibility for recovery during working hours, and acknowledging worries about infection. Young healthcare workers and staff who are relocated due to the pandemic warrant special attention.
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| 6. |
- Zhang, C., et al.
(författare)
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The acute effect of metabolic cofactor supplementation: a potential therapeutic strategy against non-alcoholic fatty liver disease
- 2020
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Ingår i: Molecular Systems Biology. - : EMBO. - 1744-4292. ; 16:4
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Tidskriftsartikel (refereegranskat)abstract
- The prevalence of non-alcoholic fatty liver disease (NAFLD) continues to increase dramatically, and there is no approved medication for its treatment. Recently, we predicted the underlying molecular mechanisms involved in the progression of NAFLD using network analysis and identified metabolic cofactors that might be beneficial as supplements to decrease human liver fat. Here, we first assessed the tolerability of the combined metabolic cofactors including l-serine, N-acetyl-l-cysteine (NAC), nicotinamide riboside (NR), and l-carnitine by performing a 7-day rat toxicology study. Second, we performed a human calibration study by supplementing combined metabolic cofactors and a control study to study the kinetics of these metabolites in the plasma of healthy subjects with and without supplementation. We measured clinical parameters and observed no immediate side effects. Next, we generated plasma metabolomics and inflammatory protein markers data to reveal the acute changes associated with the supplementation of the metabolic cofactors. We also integrated metabolomics data using personalized genome-scale metabolic modeling and observed that such supplementation significantly affects the global human lipid, amino acid, and antioxidant metabolism. Finally, we predicted blood concentrations of these compounds during daily long-term supplementation by generating an ordinary differential equation model and liver concentrations of serine by generating a pharmacokinetic model and finally adjusted the doses of individual metabolic cofactors for future human clinical trials.
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| 7. |
- Palmquist, Anders, 1977, et al.
(författare)
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Complex geometry and integrated macro-porosity: Clinical applications of electron beam melting to fabricate bespoke bone-anchored implants
- 2023
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Ingår i: Acta Biomaterialia. - : Elsevier BV. - 1742-7061 .- 1878-7568. ; 156, s. 125-145
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Forskningsöversikt (refereegranskat)abstract
- The last decade has witnessed rapid advancements in manufacturing technologies for biomedical implants. Additive manufacturing (or 3D printing) has broken down major barriers in the way of producing complex 3D geometries. Electron beam melting (EBM) is one such 3D printing process applicable to metals and alloys. EBM offers build rates up to two orders of magnitude greater than comparable laser-based technologies and a high vacuum environment to prevent accumulation of trace elements. These features make EBM particularly advantageous for materials susceptible to spontaneous oxidation and nitrogen pick-up when exposed to air (e.g., titanium and titanium-based alloys). For skeletal reconstruction(s), anatomical mimickry and integrated macro-porous architecture to facilitate bone ingrowth are undoubtedly the key features of EBM manufactured implants. Using finite element modelling of physiological loading conditions, the design of a prosthesis may be further personalised. This review looks at the many unique clinical applications of EBM in skeletal repair and the ground-breaking innovations in prosthetic rehabilitation. From a simple acetabular cup to the fifth toe, from the hand-wrist complex to the shoulder, and from vertebral replacement to cranio-maxillofacial reconstruction, EBM has experienced it all. While sternocostal reconstructions might be rare, the repair of long bones using EBM manufactured implants is becoming exceedingly frequent. Despite the various merits, several challenges remain yet untackled. Nevertheless, with the capability to produce osseointegrating implants of any conceivable shape/size, and permissive of bone ingrowth and functional loading, EBM can pave the way for numerous fascinating and novel applications in skeletal repair, regeneration, and rehabilitation. Statement of significance: Electron beam melting (EBM) offers unparalleled possibilities in producing contaminant-free, complex and intricate geometries from alloys of biomedical interest, including Ti6Al4V and CoCr. We review the diverse range of clinical applications of EBM in skeletal repair, both as mass produced off-the-shelf implants and personalised, patient-specific prostheses. From replacing large volumes of disease-affected bone to complex, multi-material reconstructions, almost every part of the human skeleton has been replaced with an EBM manufactured analog to achieve macroscopic anatomical-mimickry. However, various questions regarding long-term performance of patient-specific implants remain unaddressed. Directions for further development include designing personalised implants and prostheses based on simulated loading conditions and accounting for trabecular bone microstructure with respect to physiological factors such as patient's age and disease status.
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| 8. |
- Berglund, Fanny, et al.
(författare)
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Evidence for wastewaters as environments where mobile antibiotic resistance genes emerge
- 2023
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Ingår i: Communications Biology. - : Springer Science and Business Media LLC. - 2399-3642. ; 6
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Tidskriftsartikel (refereegranskat)abstract
- The emergence and spread of mobile antibiotic resistance genes (ARGs) in pathogens have become a serious threat to global health. Still little is known about where ARGs gain mobility in the first place. Here, we aimed to collect evidence indicating where such initial mobilization events of clinically relevant ARGs may have occurred. We found that the majority of previously identified origin species did not carry the mobilizing elements that likely enabled intracellular mobility of the ARGs, suggesting a necessary interplay between different bacteria. Analyses of a broad range of metagenomes revealed that wastewaters and wastewater-impacted environments had by far the highest abundance of both origin species and corresponding mobilizing elements. Most origin species were only occasionally detected in other environments. Co-occurrence of origin species and corresponding mobilizing elements were rare in human microbiota. Our results identify wastewaters and wastewater-impacted environments as plausible arenas for the initial mobilization of resistance genes.
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| 9. |
- Ge, Chenjie, 1991, et al.
(författare)
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Enlarged Training Dataset by Pairwise GANs for Molecular-Based Brain Tumor Classification
- 2020
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Ingår i: IEEE Access. - 2169-3536 .- 2169-3536. ; 8:1, s. 22560-22570
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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.
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| 10. |
- Fristedt, Sofi, 1969-, et al.
(författare)
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Digi-Do: a digital information tool to support patients with breast cancer before, during, and after start of radiotherapy treatment: an RCT study protocol
- 2021
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Ingår i: BMC Medical Informatics and Decision Making. - : Springer Science and Business Media LLC. - 1472-6947. ; 21:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: Radiation Therapy (RT) is a common treatment after breast cancer surgery and a complex process using high energy X-rays to eradicate cancer cells, important in reducing the risk of local recurrence. The high-tech environment and unfamiliar nature of RT can affect the patient's experience of the treatment. Misconceptions or lack of knowledge about RT processes can increase levels of anxiety and enhance feelings of being unprepared at the beginning of treatment. Moreover, the waiting time is often quite long. The primary aim of this study will be to evaluate whether a digital information tool with VR-technology and preparatory information can decrease distress as well as enhance the self-efficacy and health literacy of patients affected by breast cancer before, during, and after RT. A secondary aim will be to explore whether the digital information tool increase patient flow while maintaining or increasing the quality of care. Method: The study is a prospective and longitudinal RCT study with an Action Research participatory design approach including mixed-methods data collection, i.e., standardised instruments, qualitative interviews (face-to-face and telephone) with a phenomenological hermeneutical approach, diaries, observations, and time measurements, and scheduled to take place from autumn 2020 to spring 2022. The intervention group (n=80), will receive standard care and information (oral and written) and the digital information tool; and the control group (n=80), will receive standard care and information (oral and written). Study recruitment and randomisation will be completed at two centres in the west of Sweden. Discussion: Research in this area is scarce and, to our knowledge, only few previous studies examine VR as a tool for increasing preparedness for patients with breast cancer about to undergo RT that also includes follow-ups six months after completed treatment. The participatory approach and design will safeguard the possibilities to capture the patient perspective throughout the development process, and the RCT design supports high research quality. Digitalisation brings new possibilities to provide safe, person-centred information that also displays a realistic picture of RT treatment and its contexts. The planned study will generate generalisable knowledge of relevance in similar health care contexts.Trial registration: ClinicalTrials.gov Identifier: NCT04394325. Registered May 19, 2020. Prospectively registered.
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