In longitudinal cohort studies, it is often of interest to predict the risk of a terminal clinical event using longitudinal predictor data among subjects at risk by the time of the prediction. The ...at-risk population changes over time; so does the association between predictors and the outcome, as well as the accumulating longitudinal predictor history. The dynamic nature of this prediction problem has received increasing interest in the literature, but computation often poses a challenge. The widely used joint model of longitudinal and survival data often comes with intensive computation and excessive model fitting time, due to numerical optimization and the analytically intractable high-dimensional integral in the likelihood function. This problem is exacerbated when the model is fit to a large dataset or the model involves multiple longitudinal predictors with nonlinear trajectories. This challenge can be addressed from an algorithmic perspective, by a novel two-stage estimation procedure, and from a computing perspective, by Graphics Processing Unit (GPU) programming. The latter is implemented through PyTorch, an emerging deep learning framework. The numerical studies demonstrate that the proposed algorithm and software can substantially speed up the estimation of the joint model, particularly with large datasets. The numerical studies also concluded that accounting for nonlinearity in longitudinal predictor trajectories can improve the prediction accuracy in comparison to joint modeling that ignore nonlinearity.
The aim of the present study was to compare the short-term outcomes between spontaneous ventilation video-assisted thoracic surgery (SV-VATS) and mechanical ventilation video-assisted thoracic ...surgery (MV-VATS) in the elderly. All patients included in the present study underwent lobectomy, segmentectomy, or wedge resection and lymph node dissection.
A retrospective cohor.
The first affiliated hospital of Guangzhou Medical University, Guangzhou, China.
The present study included 799 elderly patients diagnosed with non-small-cell lung cancer undergoing SV-VATS or MV-VATS. After propensity score matching, 80 patients in the SV-VATS group and 80 patients in the MV-VATS group were analyzed.
Patients in the SV-VATS group received spontaneous-ventilation anesthesia, which was administered as follows: intravenous anesthesia + laryngeal mask airway + thoracic paravertebral block + visceral pleural surface anesthesia + thoracic vagus nerve block. Patients in the MV-VATS group received general endotracheal anesthesia. SV-VATS or MV-VATS was performed according to the preference of the patients.
There were no significant differences in anesthesia time (226.3 ± 79.8 v 238.5 ± 66.2 min; p = 0.44), surgery time (166.2 ± 102.6 v 170.1 ± 83.4 min; p = 0.66), and number of dissected lymph nodes (5.3 ± 7.5 v 4.4 ± 7.4; p = 0.23) between the two groups. There were significant differences in intraoperative bleeding (61.5 ± 165.1 v 82.2 ± 116.9 mL; p < 0.001). After surgery, the two groups were statistically comparable in terms of hospitalization (17.6 ± 7.6 v 17.2 ± 6.9 days; p = 0.95) and incidence of complications (7.5% v 13.8%; p = 0.20), while there were significant differences in chest tube duration (6.1 ± 3.3 v 4.5 ± 1.2 days; p < 0.001).
SV-VATS is feasible and as safe as MV-VATS, and it could be considered as an alternative treatment for the elderly.
•We conducted a systematic review and meta-analysis to update the evidence for the association between HSV-1 infection and AD.•There are 21 studies containing 3566 participants included in our ...study.•We found that HSV-1 infection is associated with risk of AD: pooled OR 1.40 (95% CI: 1.13–1.75; I2 = 3%, P = 0.42).•Our up-to-date systematic review and meta-analysis suggest that HSV-1 infection is a risk factor of Alzheimer’s Disease.
There is growing evidence demonstrating the relationship between herpes simplex virus type 1 (HSV-1) infection and Alzheimer’s disease (AD). We searched PubMed, Embase, and Cochrane databases for relevant articles. The Newcastle-Ottawa Scale (NOS) was used to evaluate the qualities of these studies. Pooled odds ratios (ORs) with 95% confidence intervals (CIs) were calculated using random-effects models. We also performed subgroup analyses stratified by apolipoprotein ε4 (APOE ε4), NOS score, and the method of confirming AD. A total of 21 studies between 1990 and 2020 were identified. The pooled OR suggested that HSV-1 infection is a risk factor of AD: pooled OR 1.40 (95% CI: 1.13–1.75; I2 = 3%, P = 0.42). In the subgroup analyses, the pooled ORs of HSV-1 infection associated with AD were 0.75 (95% CI: 0.24–2.37) among the APOE ε4-positive individuals; 0.85 (95% CI: 0.61–1.17) among the APOE ε4-negative individuals; 1.51 (95% CI: 1.10–2.06) in the high NOS score studies; 1.23 (95% CI: 0.85–1.76) in the moderate NOS score studies; 1.47 (95% CI: 1.16–1.87) in the clinical diagnosis group, and 1.20 (95% CI: 0.77–1.87) in the autopsy group. Our up-to-date systematic review and meta-analysis suggest that HSV-1 infection is a risk factor of AD.
As two fundamental problems, graph cuts and graph matching have been intensively investigated over the decades, resulting in vast literature in these two topics respectively. However the way of ...jointly applying and solving graph cuts and matching receives few attention. In this paper, we first formalize the problem of simultaneously cutting a graph into two partitions i.e. graph cuts and establishing their correspondence i.e. graph matching. Then we develop an optimization algorithm by updating matching and cutting alternatively, provided with theoretical analysis. The efficacy of our algorithm is verified on both synthetic dataset and real-world images containing similar regions or structures.
Background: Previous studies have shown that the levels of serum tumor markers CEA and CA19-9 were related to chemoradiotherapy. Therefore, it has been assumed that dynamic monitoring of these ...markers could predict the prognosis of stage II/III rectal cancer (RC). Therefore, this study proposed to evaluate the prognostic value of changes in serum tumor biomarkers for stage II/III RC patients undergoing neoadjuvant chemoradiotherapy (NCRT) followed by total mesorectal excision (TME). Methods: A total of 217 patients with stage II/III RC receiving NCRT followed by TME were retrospectively analyzed. Serum CEA and CA199 levels were measured within one week before NCRT and one week before TME. The optimal cut-off points of ECEA% and ECA199% for prognosis prediction were calculated by receiver operating characteristics (ROC) analysis. Independent prognostic predictors were identified by univariate and multivariate Cox regression analyses. To avoid the efficiency of ECEA% and ECA199% on serum tumor biomarker change (STBC) score, two models including and excluding ECEA% and ECA199% were established separately in multivariate analysis. Results: The optimal cut-off point for ECEA% and ECA199% were -30.29% and 20.30%, respectively. Univariate analysis showed that ECEA%, ECA199%, STBC score, ypT staging and yN staging could predict OS. ypT staging and STBC score could predict DFS. In multivariate analysis, only ECA199% (HR = 0.468, 95% CI: 0.220-0.994, p = 0.048), ypT staging (HR = 0.420, 95% CI: 0.182-0.970, p = 0.042), and STBC score (HR = 0.204, 95% CI: 0.078-0.532, p = 0.001) were independently related to OS; and STBC score (HR = 0.412, 95% CI: 0.216-0.785, p=0.007) and ypT staging (HR = 0.421, 95% CI: 0.224-0.792, p = 0.007) were independently related to DFS. Conclusion: We established a combined STBC score to predict the prognosis of stage II/III RC patients receiving NCRT followed by TME. The predictive value of the combined score was stronger than a single marker alone and even stronger than several pathological indicators. Keywords: neoadjuvant chemoradiotherapy, stage II/III rectal cancer, total mesorectal excision, prognosis, STBC score
Continuous collision detection (CCD) is a process to interpolate the trajectory of polygons and detect collisions between successive time steps. However, this process is time-consuming, especially ...for a large number of moving polygons. In this paper, we present a parallel CCD algorithm, which aims to accelerate
N
-body rigid CCD culling by distributing the load across a distributed-memory system. This algorithm is particularly suitable for large-scale distributed simulations. Experimental results, based on a message passing interface implementation, demonstrate that our approach is more computationally efficient than existing sequential CCD approaches.
Ancestral genome reconstruction has attracted increasing interests from both biologists and computer scientists. It has been conducted using various evolutionary models ever since comparative ...genomics moved from sequence data to gene order data. We propose a Flexible Ancestral Reconstruction Model, FARM, based on the maximum likelihood and weighted maximum matching algorithms, to infer ancestral gene orders. This will accommodate various evolutionary scenarios, including not only genomic rearrangements, but also insertion/deletions (indels), segment duplications, and whole genome duplications. We evaluate this work by using various simulated evolution experiments while comparing FARM to existing methods, like InferCarsPro, GASTS and PMAG++. FARM shows significant improvement in running time and the final assembling process and, therefore, can be used in large-scale real biological data ancestral inference.
We present a novel algorithm to partition large 3D meshes for GPU-based decompression. Our formulation focuses on minimizing the replicated vertices between patches, and balancing the numbers of ...faces of patches for efficient parallel computing. First we generate a topology model of the original mesh and remove vertex positions. Then we assign the centers of patches using geodesic farthest point sampling and cluster the faces according to geodesic distance. After the segmentation we swap boundary faces to fix jagged boundaries and store the boundary vertices for whole-mesh preservation. The decompression of each patch runs on a thread of GPU, we have evaluated its performance on various large benchmarks. In practice, the GPU-based decompression algorithm runs more than 48X faster with that on the CPU.
Ambiguous gene names in the biomedical literature are a barrier to accurate information extraction. To overcome this hurdle, we generated Ontology Fingerprints for selected genes that are relevant ...for personalized cancer therapy. These Ontology Fingerprints were used to evaluate the association between genes and biomedical literature to disambiguate gene names. We obtained 93.6% precision for the test gene set and 80.4% for the area under a receiver-operating characteristics curve for gene and article association. The core algorithm was implemented using a graphics processing unit-based MapReduce framework to handle big data and to improve performance. We conclude that Ontology Fingerprints can help disambiguate gene names mentioned in text and analyse the association between genes and articles. Database URL: http://www.ontologyfingerprint.org
SCRFD Chen, Ming; Du, Peng; Zhao, Jieyi
Proceedings of the 2018 5th International Conference on Biomedical and Bioinformatics Engineering,
11/2018
Conference Proceeding
Rib fracture is a very common type of chest injury. Currently, the diagnosis of rib fracture is usually performed by chest CT. Due to the large number of chest CT slices, the diagnosis is very time- ...consuming. Especially for the detection of non-displaced fractures with very fine fracture locations and multiple fractures in the same patient's ribs, the missed diagnosis rate is still very high. To improve the detection precision, we propose a spatial coherence based rib fracture detection method, first we employ a novel feature extraction method to extract the rib region from CT slice, followed by a novel spatial coherence based convolutional neural network to recognize whether fracture occurs in the rib region. We have compared our method with currently popular object detection method. Experiment results show that our method has drastically improvements on precision and performance over previous methods.
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