Result 1 - 10 of total 1570
Soaring aspirations
1936
| Author's details | [Regie: Wu Yonggang] |
|---|---|
| Language | Chinese |
| Size | 2 VCDs, 93 Min |
| Publishing place | China |
| Document type | Book |
| Note | Audiosprache: Chinesisch |
| Database | Former special subject collection: coastal and deep sea fishing |
Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.
2023 Volume 55, Issue S 01, Page(s) E1221–E1222
| Language | English |
|---|---|
| Publishing date | 2023-12-08 |
| Publishing country | Germany |
| Document type | Journal Article |
| ZDB-ID | 80120-3 |
| ISSN | 1438-8812 ; 0013-726X |
| ISSN (online) | 1438-8812 |
| ISSN | 0013-726X |
| DOI | 10.1055/a-2216-0906 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
| Zs.A 669: Show issues | Location: Je nach Verfügbarkeit (siehe Angabe bei Bestand) bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular Jg. 1995 - 2021: Lesesall (1.OG) ab Jg. 2022: Lesesaal (EG) |
|||
| Zs.MO 162: Show issues |
This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.
European heart journal. Cardiovascular Imaging
2023 Volume 25, Issue 4, Page(s) e137
| MeSH term(s) | Humans ; Heart Septal Defects, Ventricular ; Echocardiography |
|---|---|
| Language | English |
| Publishing date | 2023-11-27 |
| Publishing country | England |
| Document type | Journal Article |
| ZDB-ID | 2638345-7 |
| ISSN | 2047-2412 ; 2047-2404 |
| ISSN (online) | 2047-2412 |
| ISSN | 2047-2404 |
| DOI | 10.1093/ehjci/jead289 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
| Zs.A 5614: Show issues | Location: Je nach Verfügbarkeit (siehe Angabe bei Bestand) bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular Jg. 1995 - 2021: Lesesall (2.OG) ab Jg. 2022: Lesesaal (EG) |
This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.
IEEE transactions on medical imaging
2024 Volume 43, Issue 1, Page(s) 405–415
Abstract: This paper investigates how to effectively mine contextual information among sequential images and jointly model them in medical imaging tasks. Different from state-of-the-art methods that model sequential correlations via point-wise token encoding, this ...
| Abstract | This paper investigates how to effectively mine contextual information among sequential images and jointly model them in medical imaging tasks. Different from state-of-the-art methods that model sequential correlations via point-wise token encoding, this paper develops a novel hierarchical pattern-aware tokenization strategy. It handles distinct visual patterns independently and hierarchically, which not only ensures the full flexibility of attention aggregation under different pattern representations but also preserves both local and global information simultaneously. Based on this strategy, we propose a Pattern-Aware Transformer (PATrans) featuring a global-local dual-path pattern-aware cross-attention mechanism to achieve hierarchical pattern matching and propagation among sequential images. Furthermore, PATrans is plug-and-play and can be seamlessly integrated into various backbone networks for diverse downstream sequence modeling tasks. We demonstrate its general application paradigm across four domains and five benchmarks in video object detection and 3D volumetric semantic segmentation tasks, respectively. Impressively, PATrans sets new state-of-the-art across all these benchmarks, i.e., CVC-Video (92.3% detection F1), ASU-Mayo (99.1% localization F1), Lung Tumor (78.59% DSC), Nasopharynx Tumor (75.50% DSC), and Kidney Tumor (87.53% DSC). Codes and models are available at https://github.com/GGaoxiang/PATrans. |
|---|---|
| MeSH term(s) | Humans ; Lung Neoplasms ; Semantics |
| Language | English |
| Publishing date | 2024-01-02 |
| Publishing country | United States |
| Document type | Journal Article |
| ZDB-ID | 622531-7 |
| ISSN | 1558-254X ; 0278-0062 |
| ISSN (online) | 1558-254X |
| ISSN | 0278-0062 |
| DOI | 10.1109/TMI.2023.3306468 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
| Zs.A 2546: Show issues | Location: Je nach Verfügbarkeit (siehe Angabe bei Bestand) bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular Jg. 1995 - 2021: Lesesall (2.OG) ab Jg. 2022: Lesesaal (EG) |
This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.
Computational biology and chemistry
2024 Volume 110, Page(s) 108041
Abstract: Accumulating clinical studies have consistently demonstrated that the microbes in the human body closely interact with the human host, actively participating in the regulation of drug effectiveness. Identifying the associations between microbes and drugs ...
| Abstract | Accumulating clinical studies have consistently demonstrated that the microbes in the human body closely interact with the human host, actively participating in the regulation of drug effectiveness. Identifying the associations between microbes and drugs can facilitate the development of drug discovery, and microbes have become a new target in antimicrobial drug development. However, the discovery of microbe-drug associations relies on clinical or biological experiments, which are not only time-consuming but also financially burdensome. Thus, the utilization of computational methods to predict microbe-drug associations holds promise for reducing costs and enhancing the efficiency of biological experiments. Here, we introduce a new computational method, called HKFGCN (Heterogeneous information Kernel Fusion Graph Convolution Network), to predict the microbe-drug associations. Instead of extracting feature from a single network in previous studies, HKFGCN separately extracts topological information features from different networks, and further refines them by generating Gaussian kernel features. HKFGCN consists of three main steps. Firstly, we constructed two similarity networks and a microbe-drug association network based on numerous biological data. Second, we employed two types of encoders to extract features from these networks. Next, Gaussian kernel features were obtained from the drug and microbe features at each layer. Finally, we reconstructed the bipartite microbe-drug graph based on the learned representations. Experimental results demonstrate the excellent performance of the HKFGCN model across different datasets using the cross-validation scheme. Additionally, we conduced case studies on human immunodeficiency virus, and the results were corroborated by existing literatures. The prediction model's code is available at https://github.com/roll-of-bubble/HKFGCN. |
|---|---|
| Language | English |
| Publishing date | 2024-03-02 |
| Publishing country | England |
| Document type | Journal Article |
| ISSN | 1476-928X |
| ISSN (online) | 1476-928X |
| DOI | 10.1016/j.compbiolchem.2024.108041 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.
Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.
2024 Volume 15, Issue 16, Page(s) 6044–6052
Abstract: The discovery of new antibacterials within the vast chemical space is crucial in combating drug-resistant bacteria such as methicillin- ... ...
| Abstract | The discovery of new antibacterials within the vast chemical space is crucial in combating drug-resistant bacteria such as methicillin-resistant |
|---|---|
| Language | English |
| Publishing date | 2024-03-26 |
| Publishing country | England |
| Document type | Journal Article |
| ZDB-ID | 2559110-1 |
| ISSN | 2041-6539 ; 2041-6520 |
| ISSN (online) | 2041-6539 |
| ISSN | 2041-6520 |
| DOI | 10.1039/d3sc06441g |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.
2024 Volume 102, Issue 52, Page(s) e36702
Abstract: Background: Virtual reality (VR)-based pulmonary rehabilitation has been used in the management of chronic obstructive pulmonary disease (COPD). The efficacy of VR-based pulmonary rehabilitation for improving lung function in patients with COPD is ... ...
| Abstract | Background: Virtual reality (VR)-based pulmonary rehabilitation has been used in the management of chronic obstructive pulmonary disease (COPD). The efficacy of VR-based pulmonary rehabilitation for improving lung function in patients with COPD is controversial. Therefore, the aim of this meta-analysis was to evaluate the efficacy of VR combined with pulmonary rehabilitation for lung function in patients with COPD. Methods: This study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The search was performed in the Cochrane Library, EMBASE, Web of Science, PubMed, and China National Knowledge Infrastructure databases from inception to February 1, 2023. All included studies were randomized controlled trials that assessed VR combined with pulmonary rehabilitation for COPD patients. The effect size was calculated with standardized mean difference (SMD) and its 95% confidence interval (CI). The Cochrane Collaboration tool was used to assess the risk of bias. Publication bias was assessed by Egger test. Results: A total of 11 studies met the inclusion criteria and were included in this study. The combined effect size showed that VR combined with pulmonary rehabilitation was more effective than pulmonary rehabilitation alone at improving forced expiratory volume in 1 second% (SMD: 0.51; 95% CI 0.19,0.82; P = .002), forced expiratory volume in 1 second/forced vital capacity (SMD: 0.71; 95% CI 0.49,0.93; P < .001), dyspnea (SMD: -0.44; 95% CI -0.66, -0.22; P < .001), and 6-minute walking test (SMD: 059; 95% CI 0.39, 0.79; P < .001). In addition, the VR combined with pulmonary rehabilitation improved depression (SMD: -0.34; 95% CI -0.05, -0.03; P = .033) and anxiety mood (SMD: -0.57; 95% CI -1.11, -0.04; P = .036) compared with the pulmonary rehabilitation group. Conclusion: This meta-analysis indicated that VR regimens could be used to enhance the therapeutic effect of pulmonary rehabilitation in patients with COPD. However, as a rapidly evolving field, more well-designed randomized controlled trials are needed to determine the impact of VR-based pulmonary rehabilitation on COPD patients. |
|---|---|
| MeSH term(s) | Humans ; China ; Pulmonary Disease, Chronic Obstructive/rehabilitation ; Quality of Life ; Randomized Controlled Trials as Topic ; Virtual Reality |
| Language | English |
| Publishing date | 2024-01-11 |
| Publishing country | United States |
| Document type | Meta-Analysis ; Journal Article |
| ZDB-ID | 80184-7 |
| ISSN | 1536-5964 ; 0025-7974 |
| ISSN (online) | 1536-5964 |
| ISSN | 0025-7974 |
| DOI | 10.1097/MD.0000000000036702 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
| Ua VI Zs.171: Show issues | Location: Je nach Verfügbarkeit (siehe Angabe bei Bestand) bis Jg. 2021: Bestellungen von Artikeln über das Online-Bestellformular ab Jg. 2022: Lesesaal (EG) |
This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.
2023 Volume 14, Page(s) 1253520
Abstract: Background: ...
| Abstract | Background: |
|---|---|
| Language | English |
| Publishing date | 2023-09-07 |
| Publishing country | Switzerland |
| Document type | Systematic Review |
| ZDB-ID | 2587355-6 |
| ISSN | 1663-9812 |
| ISSN | 1663-9812 |
| DOI | 10.3389/fphar.2023.1253520 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.
Journal of colloid and interface science
2023 Volume 658, Page(s) 553–561
Abstract: Layered sodium vanadium materials have aroused increasing interest owing to their open layered structures and high theoretical capacity. Nevertheless, the strong electrostatic interactions between vanadium oxide layers and intercalated ... ...
| Abstract | Layered sodium vanadium materials have aroused increasing interest owing to their open layered structures and high theoretical capacity. Nevertheless, the strong electrostatic interactions between vanadium oxide layers and intercalated Zn |
|---|---|
| Language | English |
| Publishing date | 2023-12-18 |
| Publishing country | United States |
| Document type | Journal Article |
| ZDB-ID | 241597-5 |
| ISSN | 1095-7103 ; 0021-9797 |
| ISSN (online) | 1095-7103 |
| ISSN | 0021-9797 |
| DOI | 10.1016/j.jcis.2023.12.104 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
| Z 71/707: Show issues |
This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.
Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.
2023 Volume 46, Issue 7, Page(s) 2934–2935
| MeSH term(s) | Humans ; Echocardiography, Transesophageal ; Mitral Valve Insufficiency/diagnostic imaging ; Mitral Valve Insufficiency/etiology ; Mitral Valve Insufficiency/surgery ; Papillary Muscles/diagnostic imaging ; Heart Valve Prosthesis |
|---|---|
| Language | English |
| Publishing date | 2023-02-16 |
| Publishing country | Netherlands |
| Document type | Letter |
| ZDB-ID | 1068461-x |
| ISSN | 0219-3108 ; 1015-9584 |
| ISSN (online) | 0219-3108 |
| ISSN | 1015-9584 |
| DOI | 10.1016/j.asjsur.2023.02.013 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
| Zs.B 2831: Show issues | Location: Je nach Verfügbarkeit (siehe Angabe bei Bestand) bis Jg. 2021: Bestellungen von Artikeln über das Online-Bestellformular ab Jg. 2022: Lesesaal (EG) |
This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.