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1.
PurposeAccording to the social determinants of health framework, income inequality is a potential risk factor for adverse mental health. However, few studies have explored the mechanisms suspected to mediate this relationship. The current study addresses this gap through a mediation analysis to determine if social support and community engagement act as mediators linking neighbourhood income inequality to maternal anxiety and depressive symptoms within a cohort of new mothers living in the City of Calgary, Canada.MethodsData collected at three years postpartum from mothers belonging to the All Our Families (AOF) cohort were used in the current study. Maternal data were collected between 2012 and 2015 and linked to neighbourhood socioeconomic data from the 2006 Canadian Census. Income inequality was measured using Gini coefficients derived from 2006 after-tax census data. Generalized structural equation models were used to quantify the associations between income inequality and mental health symptoms, and to assess the potential direct and indirect mediating effects of maternal social support and community engagement.ResultsIncome inequality was not significantly associated with higher depressive symptoms (β = 0.32, 95%CI = −0.067, 0.70), anxiety symptoms (β = 0.11, 95%CI = −0.39, 0.60), or lower social support. Income inequality was not associated with community engagement. For the depression models, higher social support was significantly associated with lower depressive symptoms (β = −0.13, 95%CI = −0.15, −0.097), while community engagement was not significantly associated with depressive symptoms (β = 0.059, 95%CI = −0.15, 0.27). Similarly, for the anxiety models, lower anxiety symptoms were significantly associated with higher levels of social support (β = −0.17, 95%CI = −0.20, −0.13) but not with higher levels of community engagement (β = 0.14, 95%CI = −0.14, 0.41).ConclusionThe current study did not find clear evidence for social support or community engagement mediating the relationship between neighbourhood income inequality and maternal mental health. Future investigations should employ a broader longitudinal approach to capture changes in income inequality, potential mediators, and mental health symptomatology over time.  相似文献   
2.
ObjectiveWe aimed at developing a pilot version of an app (Rosa) that can perform digital conversations with breast or ovarian cancer patients about genetic BRCA testing, using chatbot technology, to identify best practices for future patient-focused chatbots.MethodsWe chose a commercial chatbot platform and participatory methodology with a team of patient representatives, IT engineers, genetic counselors and clinical geneticists, within a nationwide collaboration. An iterative approach ensured extensive user and formal usability testing during the development process.ResultsThe development phase lasted for two years until the pilot version was completed in December 2019. The iteration steps disclosed major challenges in the artificial intelligence (AI)-based matching of user provided questions with predefined information in the database, leading initially to high level of fallback answers. We therefore developed strategies to reduce potential language ambiguities (e.g. BRCA1 vs BRCA2) and overcome dialogue confusion. The first prototype contained a database with 500 predefined questions and 67 corresponding predefined answers, while the final version included 2257 predefined questions and 144 predefined answers. Despite the limited AI functionality of the chatbot, the testing revealed that the users liked the layout and found the chatbot trustworthy and reader friendly.ConclusionsBuilding a health chatbot is challenging, expensive and time consuming with today’s technology. The users had a positive attitude to the chatbot, and would use it in a real life setting, if given to them by health care personnel.Practice implicationsWe here present a framework for future health chatbot initiatives. The participatory methodology in combination with an iterative approach ensured that the patient perspective was incorporated at every level of the development process. We strongly recommend this approach in patient-centered health innovations.  相似文献   
3.
Radiomics is the quantitative analysis of standard-of?care medical imaging; the information obtained can be applied within clinical decision support systems to create diagnostic, prognostic, and/or predictive models. Radiomics analysis can be performed by extracting hand-crafted radiomics features or via deep learning algorithms. Radiomics has evolved tremendously in the last decade, becoming a bridge between imaging and precision medicine. Radiomics exploits sophisticated image analysis tools coupled with statistical elaboration to extract the wealth of information hidden inside medical images, such as computed tomography (CT), magnetic resonance (MR), and/or Positron emission tomography (PET) scans, routinely performed in the everyday clinical practice. Many efforts have been devoted in recent years to the standardization and validation of radiomics approaches, to demonstrate their usefulness and robustness beyond any reasonable doubts. However, the booming of publications and commercial applications of radiomics approaches warrant caution and proper understanding of all the factors involved to avoid “scientific pollution” and overly enthusiastic claims by researchers and clinicians alike. For these reasons the present review aims to be a guidebook of sorts, describing the process of radiomics, its pitfalls, challenges, and opportunities, along with its ability to improve clinical decision-making, from oncology and respiratory medicine to pharmacological and genotyping studies.  相似文献   
4.
人工智能在心电图中的应用是心血管领域正在发生变革的一个重要方向。近年来,先进的人工智能技术,如深度学习,卷积神经网络等,已经实现了对心电图的快速、类似于人类的判读,而多层神经网络可以精确地检测到人类判读者基本无法识别的信号和模式,使心电图成为一个强大的“生物标志物”。大量的数字化心电图已经被用于开发人工智能模型,可检测阵发性心房颤动、左心室功能障碍、心肌病以及高钾血症、瓣膜疾病等异常情况。在这篇综述中,我们总结了人工智能辅助的心电图诊断在心血管疾病中的应用现状,讨论并评估了其临床意义、局限性和发展前景。  相似文献   
5.

近年来,随着计算机学科的进步与学科交叉融合的推进,人工智能(AI)在医学领域呈现出迅猛发展的态势,在眼科学也取得了许多突破性进展。既往AI在眼科学的应用研究大多集中在糖尿病视网膜病变、年龄相关性黄斑变性等眼底疾病。近年来,随着AI学习算法的改进以及大数据的开发利用,AI在眼科学的应用范围得以进一步拓展,越来越多的研究开始将AI应用于眼表疾病。本文综述了AI在圆锥角膜、翼状胬肉及角膜炎等眼表疾病中的相关研究和应用,探讨当前AI在眼科学临床应用中面临的挑战与机遇,并对其未来发展前景进行展望,旨在为眼科AI的发展提供新思路。  相似文献   

6.
7.
《Dental materials》2022,38(5):778-788
ObjectivesTo evaluate two-body wear (2BW) and three-body wear (3BW) of different CAD/CAM and direct restorative materials against zirconia using a dual-axis chewing simulator and an ACTA wear machine.Methods3 CAD-CAM resin-based composite or polymer infiltrated ceramic network blocs, 1 lithium disilicate CAD-CAM ceramic (LS2), 3 direct resin composites, amalgam and bovine enamel were tested. For 2BW, 8 flat specimens per material were produced, grinded, polished, stored wet (37 °C, 28d) and tested (49 N, 37 °C, 1,200,000 cycles) against zirconia. For 3BW, specimens (n = 10) were stored accordingly, and tested against a zirconia antagonist wheel (3Y-TZP, d = 20 mm, h = 6 mm; 200,000 cycles, F = 15 N, f = 1 Hz, 15% slip) in millet seed suspension. Wear resistance was analysed in a 3D optical non-contact profilometer, measuring vertical wear depth and volume loss for 2BW and mean wear depth and roughness (Ra) for 3BW. Vickers hardness (15 s, HV2) was measured. Statistical analysis was performed using non-parametric tests (Mann-Whitney-U test, p < 0.05).Results2BW and 3BW have a different impact on material surfaces. Similar wear resistance was observed for direct and indirect resin based materials with analogous filler configurations in both methods. Bovine enamel exhibited the best wear resistance in 2BW, but the least wear resistance in 3BW against zirconia. Regarding 2BW, a direct/indirect composite material pair of the same manufacturer showed the significantly highest mean volume losses (2.72/2.85 mm³), followed by LS2 (1.41 mm³). LS2 presented the best wear resistance in 3BW (mean wear depth 2.85 µm), combined with the highest mean Vickers hardness (598 MPa). No linear correlation was found between Vickers hardness and both wear testing procedures. The zirconia antagonists showed no recordable signs of wear.SignificanceDental restorative materials behave differently in 2BW and 3BW laboratory testing. Vickers hardness testing alone cannot hold for a correlation with wear behavior of materials. Micromorphological investigation of material composition can reveal insights in wear mechanisms related to variations in filler technologies.  相似文献   
8.
ObjectiveAddress model drift in a machine learning (ML) model for predicting diagnostic imaging follow-up using data augmentation with more recent data versus retraining new predictive models.MethodsThis institutional review board–approved retrospective study was conducted January 1, 2016, to December 31, 2020, at a large academic institution. A previously trained ML model was trained on 1,000 radiology reports from 2016 (old data). An additional 1,385 randomly selected reports from 2019 to 2020 (new data) were annotated for follow-up recommendations and randomly divided into two sets: training (n = 900) and testing (n = 485). Support vector machine and random forest (RF) algorithms were constructed and trained using 900 new data reports plus old data (augmented data, new models) and using only new data (new data, new models). The 2016 baseline model was used as comparator as is and trained with augmented data. Recall was compared with baseline using McNemar’s test.ResultsFollow-up recommendations were contained in 11.3% of reports (157 or 1,385). The baseline model retrained with new data had precision = 0.83 and recall = 0.54; none significantly different from baseline. A new RF model trained with augmented data had significantly better recall versus the baseline model (0.80 versus 0.66, P = .04) and comparable precision (0.90 versus 0.86).DiscussionML methods for monitoring follow-up recommendations in radiology reports suffer model drift over time. A newly developed RF model achieved better recall with comparable precision versus simply retraining a previously trained original model with augmented data. Thus, regularly assessing and updating these models is necessary using more recent historical data.  相似文献   
9.
ObjectiveTo develop a prediction model for survival of patients with coronary artery disease (CAD) using health conditions beyond cardiovascular risk factors, including maximal exercise capacity, through the application of machine learning (ML) techniques.MethodsAnalysis of data from a retrospective cohort linking clinical, administrative, and vital status databases from 1995 to 2016 was performed. Inclusion criteria were age 18 years or older, diagnosis of CAD, referral to a cardiac rehabilitation program, and available baseline exercise test results. Primary outcome was death from any cause. Feature selection was performed using supervised and unsupervised ML techniques. The final prognostic model used the survival tree (ST) algorithm.ResultsFrom the cohort of 13,362 patients (60±11 years; 2400 [18%] women), 1577 died during a median follow-up of 8 years (interquartile range, 4 to 13 years), with an estimated survival of 67% up to 21 years. Feature selection revealed age and peak metabolic equivalents (METs) as the features with the greatest importance for mortality prediction. Using these 2 features, the ST generated a long-term prediction with a C-index of 0.729 by splitting patients in 8 clusters with different survival probabilities (P<.001). The ST root node was split by peak METs of 6.15 or less or more than 6.15, and each patient’s subgroup was further split by age or other peak METs cut points.ConclusionApplying ML techniques, age and maximal exercise capacity accurately predict mortality in patients with CAD and outperform variables commonly used for decision-making in clinical practice. A novel and simple prognostic model was established, and maximal exercise capacity was further suggested to be one of the most powerful predictors of mortality in CAD.  相似文献   
10.
《Vaccine》2022,40(6):934-944
Respiratory Syncytial Virus (RSV) remains a leading cause of severe respiratory disease for which no licensed vaccine is available. We have previously described the derivation of an RSV Fusion protein (F) stabilized in its prefusion conformation (preF) as vaccine immunogen and demonstrated superior immunogenicity in naive mice of preF versus wild type RSV F protein, both as protein and when expressed from an Ad26 vaccine vector. Here we address the question if there are qualitative differences between the two vaccine platforms for induction of protective immunity. In naïve mice, both Ad26.RSV.preF and preF protein induced humoral responses, whereas cellular responses were only elicited by Ad26.RSV.preF. In RSV pre-exposed mice, a single dose of either vaccine induced cellular responses and strong humoral responses. Ad26-induced RSV-specific cellular immune responses were detected systemically and locally in the lungs. Both vaccines showed protective efficacy in the cotton rat model, but Ad26.RSV.preF conferred protection at lower virus neutralizing titers in comparison to RSV preF protein. Factors that may contribute to the protective capacity of Ad26.RSV.preF elicited immunity are the induced IgG2a antibodies that are able to engage Fcγ receptors mediating Antibody Dependent Cellular Cytotoxicity (ADCC), and the induction of systemic and lung resident RSV specific CD8 + T cells. These data demonstrate qualitative improvement of immune responses elicited by an adenoviral vector based vaccine encoding the RSV preF antigen compared to the subunit vaccine in small animal models which may inform RSV vaccine development.  相似文献   
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