Find research datasets worth reusing

opencc-by-4.0Dec 2018View details →

Dataset (encounter histories of female bats) used in the analysis for the paper Culina et al.: Live fast, don't die young: survival reproduction trade-offs in long-lived income breeders

Two data files (Md_capture_H, Mn_capture_H) represent the capture histories of females of two species (Myotis daubentonii = Md, and M. nattereri=Mn). These capture histories were used to run multi-event-capture-mark-recapture model, as described in the paper, and in the readme document in this data package.

opencc-by-4.0Dec 2018View details →

Dataset for "Overall Survival after Treatment for Metastatic Uveal Melanoma: A Systematic Review and Meta-Analysis"

Raw data corresponding to the paper entitled: "Overall Survival after Treatment for Metastatic Uveal Melanoma:  A Systematic Review and Meta-Analysis" published in Melanoma Research (2019) by Rantala et al.

opencc-by-4.0Dec 2024View details →

Spatial Tumor-Immune Analysis: Insights from Pathology Slides and Breast Cancer Survival

Cancer is the second leading cause of death in the US. Among the various forms of cancer, breast cancer and lung cancer are particularly significant due to their prevalence and impact. Breast cancer in particular contributing to around 30\% of all new female cases each year, while also having some of the highest mortality rates. Scientists and doctors rely on pathology slides to aid in the discovery of a cure, diagnose patients, and provide treatment. These slides play a crucial role in examining samples and identifying any abnormalities. The primary goal of this project was to analyze pathology slides from 873 cancer patients in The Cancer Genome Atlas Breast Invasive Carcinoma (TCGA-BRCA). We developed STAIN (Spatial Tumor and Immune Analysis for Novel insights) with the hypothesize that quantitative analysis of cell type specific clusters in the spatial context can lead to novel insights on patient survival. First, we identified tumor and immune cells using a HD-Yolo algorithm. Then we identify tumor clusters and immune cell clusters. Next, descriptive statistics such as Jaccard distance, Hausdorff distance, Wasserstein distance, tumor density, and immune cell density were derived and correlated with the patients survival while adjusting for clinical attributes such as patient age and tumor stage using Cox proportional Hazard models. The results discover spatial attributes and known clinical risk features associated with survival.

opencc-zeroOct 2024View details →

Analysis of the survival of agricultural exporting firms in Peru, 2009-2019

Background: At the international level, the survival of exporting companies represents a critical issue in a context of heightened uncertainty and intensified competition within the framework of the country's commercial opening. This is a context in which different companies are born and die as a result of the interaction between the market and other factors. The objective of this research was to analysis of the survival of exporting agricultural companies in Peru, 2009-2019 . To this end, data from the Commission for the Promotion of Peru for Exports and Tourism (Promperu) was utilised. Methods: The methodological contribution of the research is based on the quantitative approach, of basic type with a descriptive elk; being the population that involves a total of data of the agricultural exporting companies of Peru in the period 2009-2019 and the sample is census and the non-parametric statistical technique used was the Kaplan Meier estimate for the estimation of the survival rate. Results: Exports of Peru's non-traditional agricultural sector in FOB value have had an average annual growth of 12% in terms of FOB value and 9% in terms of volume exported; the entry rate of new agro-exporting agricultural companies reached an average growth of 2.3% and the exit rate reached an average of 2.2% in the period 2009-2019. Conclusions: The survival of exporting companies in the non-traditional agricultural sector is critical, where 89% of them survive only one year, while in the second year only 75% survive and in the sixth year only 33% survive. Keywords: Agricultural exporting firms, Export resilience, Economic sustainability, Peru's agricultural exports, Business survival analysis

opencc-by-4.0Apr 2023View details →

Data for 'Deriving spatial features from in situ proteomics imaging to enhance cancer survival analysis'

Additional data for 'Deriving spatial features from in situ proteomics imaging to enhance cancer survival analysis'

dryad40/100

Spatial survival analysis accounts for female-biased breeding dispersal and provides realistic estimates of true annual survival in migratory warblers

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publicAug 2024View details →

dryad40/100

Path analysis reveals combined winter climate and pollution effects on the survival of a marine top predator

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publicJul 2024View details →

opencc-zeroDec 2019View details →

Data from: Individual differences in behaviour explain variation in survival: a meta-analysis

Research focusing on among-individual differences in behaviour ("animal personality") has been blooming for over a decade. One of the central theories explaining the maintenance of such behavioural variation posits that individuals expressing greater "risky" behaviours should suffer higher mortality. Here, for the first time, we synthesize the existing empirical evidence for this key prediction. Our results did not support this prediction as there was no directional relationship between riskier behaviour and greater mortality; however there was a significant absolute relationship between behaviour and survival. In total, behaviour explained a significant, but small, portion (5.8%) of the variance in survival. We also found that risky (versus "shy") behavioural types live significantly longer in the wild, but not in the laboratory. This suggests that individuals expressing risky behaviours might be of overall higher quality but the lack of predation pressure and resource restrictions mask this effect in laboratory environments. Our work implies that individual differences in behaviour explain important differences in survival but not in the direction predicted by theory. Importantly, this suggests that the models predicting survival trade-offs may need revision and/or empiricists may need to reconsider their proxies of risky behaviours when testing such theory.

opencc-by-4.0Dec 2021View details →

Dataset on Modelling Rainfall Return Periods and Intensity: Survival Analysis Approach

This dataset consist Twenty years’ of annual rainfall data, obtained from  three metrological stations.  These annual rainfal were subjected to nine different probability plotting position methods, which are California, Weibull, Hazen, Adamowski, Blom, Chegodagev, Gringoten, Hirsh, and Laplace methods. The respective months and years of the rainfall was recorded. The months are recoded into halves of the year, 1 represent months in first half and 2 represents months in second year.

opencc-by-4.0Jan 2022View details →

A Survival Analysis based Volatility and Sparsity Modeling Network for Student Dropout Prediction

KDDCup15.rar and XuetangX.rar are the metadata used in the paper "A Survival Analysis based Volatility and Sparsity ModelingNetwork for Student Dropout Prediction". Both of them have be drawn from the largest MOOC platform in China, XuetangX (see https://www.xuetangx.com/). If any interested parties want to fetch the original dataset, they may follow the URLs bellow: KDDCup 2015 dataset is available at <a href="https://www.biendata.xyz/competition/kddcup2015/data/">https://www.biendata.xyz/competition/kddcup2015/data/</a>. XuetangX dataset is available at <a href="http://moocdata.cn/data/user-activity">http://moocdata.cn/data/user-activity</a>.

opencc-zeroApr 2022View details →

Maternal survival costs in an asocial mammal: Data and analysis

Abstract. Maternal characteristics, social dynamics, and environmental factors can all influence reproduction and survival as well as shape trade-offs that might arise between these components of fitness. Short-lived mammals like the golden-mantled ground squirrel (GMGS; Callospermophilus lateralis) tend to maximize effort towards current reproduction at the expense of survival but may be complicated by other aspects of the species' life history and environment.. Here, we use 25 years of data (1995-2020) collected from a population of GMGS at the Rocky Mountain Biological Research Laboratory in Gothic, Colorado, to test the effect of several maternal characteristics (e.g., age, experience, timing of litter emergence), social context (e.g., litter sex ratio, kin density), and environmental context (e.g., date of bare ground, length of vegetative growing season) on survival of reproductive female GMGS using Cox proportional hazard models. Our results indicated that social dynamics (i.e., density) and environmental conditions (i.e., standardized first day of permanent snow cover and length of growing season) explained significant variation in annual maternal survival, while maternal characteristics did not. A higher density of related breeding females and the total number of females (both related and unrelated to the focal mother) were associated with an increase in the mortality hazard. A later standardized date of the first day of permanent snow cover and a shorter growing season both reduced the maternal mortality hazard. Together, our results suggest that factors extrinsic to the squirrels affect maternal survival, and thus may also influence local population growth and dynamics in GMGS and other short-lived, territorial mammal species.

opencc-by-4.0Oct 2022View details →

1H HRMAS NMR ERETIC-CPMG dataset for survival analysis and pathological classification of gliomas

This repository contains the raw  ERETIC-CPMG HRMAS NMR data to reproduce the results reported in the following preprint: PiDeeL: Pathway-informed deep learning model for survival analysis and pathological classification of gliomas The FID spectra can be found under the FID_Samples directory. The pathological classification and survival analysis labels can be found in the Dataset_Labels.xlsx file.

opencc-by-4.0May 2024View details →

Vehicle Stock Numbers and Survival Functions for On-road Exhaust Emissions Analysis in India: 1993-2018

Guttikunda, S. K. Vehicle Stock Numbers and Survival Functions for On-road Exhaust Emissions Analysis in India: 1993-2018. Final publication online @ <a href="https://www.mdpi.com/2071-1050/16/15/6298">https://www.mdpi.com/2071-1050/16/15/6298</a>  Preprints 2024, 2024051393. <a href="https://doi.org/10.20944/preprints202405.1393.v1">https://doi.org/10.20944/preprints202405.1393.v1</a> Older publication: Re-fueling road transport for better air quality in India <a href="https://www.sciencedirect.com/science/article/abs/pii/S0301421514000020">https://www.sciencedirect.com/science/article/abs/pii/S0301421514000020</a> An informed emissions inventory can help define the baseline, use that baseline to formulate an effective air quality management plan and track progress or lack thereof, and use the results for research, innovation, and public awareness. In air quality management, at urban and regional levels, road transport remains the cornerstone of residential, commercial, and industrial activities, and the vehicle exhaust emissions maintain the position of one of the key contributing sources. In Indian cities, big and small, vehicle exhaust emissions and dust from vehicle movement on the roads, contribute to as much as 50% of particulate matter pollution in a year. So, having access to a vehicle exhaust emissions inventory that is reliable and replicable is critical for air quality management and one of the key inputs to this exercise is vehicle stock numbers. These numbers are typically obtained from vehicle registration databases, traffic surveys, and other governmental records, and often require time consuming data cleaning protocols before they can used for emissions analysis. This database provides a clean and open-access vehicle stock database, as registered and in-use fleet, for the period covering 1993 and 2018, for all India and states, along with an estimate of age-mix of the vehicles using survival functions. VAPIS Excel players included here are <ul> <li>·A method to convert fleet average speeds and fleet average travel time per day into vehicle km travelled per day.</li> <li>·A method to calculate how many additional buses are required to support odd-even or an equivalent scheme (with and without fuel mix exemptions).</li> <li>·A method to calculate total fuel wasted from idling in the city and to calculate savings from traffic management.</li> <li>·A method to calculate fuel and emission benefits of shifting a share of 2-wheeler and 4-wheeler trips to buses and non-motorized transport.</li> <li>·A method to estimate vehicle exhaust emission factors using emission standards and deterioration rates.</li> <li>·An example set of survival rates based on vehicle age for nine broad vehicle categories to convert registered number of vehicles to in-use number of vehicles.</li> <li>·A method to spatially disaggregate (grid) the total vehicle exhaust emissions using multiple grid-level proxies as weights such as density (km per grid) of various road types, population density, landuse-landcover, and information on commercial and industrial activities.</li> <li>·A library of emission factors for aerosols and gaseous species.</li> </ul>

opencc-zeroNov 2022View details →

Validation of Sepsis-3 using survival analysis and clinical evaluation of quick SOFA, SIRS, and burn-specific SIRS for sepsis in burn patients with suspected infection

Purpose: Sepsis-3 is a life-threatening organ dysfunction caused by dysregulated host responses to infection; and defined using the Sepsis-3 criteria, introduced in 2016, however, the criteria need to be validated in specific clinical fields. We investigated mortality prediction and compared the diagnostic performance of quick Sequential Organ Failure Assessment (qSOFA), systemic inflammatory response syndrome (SIRS), and burn-specific SIRS (bSIRS) in burn patients. Methods: This single-center retrospective cohort study examined burn patients in Seoul, Korea during January 2010–December 2020. Overall, 1,391 patients with suspected infection were divided into four sepsis groups using SOFA, qSOFA, SIRS, and burn-specific SIRS. Results: Hazard ratios (HRs) of all unadjusted models were statistically significant; however, the HR (0.726, p = 0.0080.001) in the SIRS ≥2 group is below 1. In the adjusted model, HRs of the SOFA ≥2 (2.426, p < 0.001), qSOFA ≥2 (7.198, p < 0.001), and SIRS ≥2 (0.575, p < 0.001) groups were significant. The diagnostic performance of dichotomized qSOFA, SIRS, and bSIRS for sepsis was defined by the Sepsis-3 criteria. The mean onset day was 4.13±2.97 according to Sepsis-3. The sensitivity of SIRS (0.989, 95% confidence interval [CI]: 0.982–0.994) was higher than that of qSOFA (0.841, 95% CI: 0.819–0.861) and bSIRS (0.803, 95% CI: 0.779–0.825). Specificities of qSOFA (0.929, 95% CI: 0.876–0.964) and bSIRS (0.922, 95% CI: 0.868–0.959) were higher than those of SIRS (0.461, 95% CI: 0.381–0.543). Conclusion: Sepsis-3 is a good alternative diagnostic tool because it reflects sepsis severity without delaying diagnosis. SIRS showed higher sensitivity than qSOFA and bSIRS and may therefore more adequately diagnose sepsis.

opencc-by-4.0Mar 2023View details →

Survival analysis after vertebral compression fractures in population over 65 years old

Background: Mortality in vertebral compression fractures (VCF) is rarely directly associated with the fracture. Lower mortality has been demonstrated when fractures are treated surgically (vertebral augmentation) versus conservatively. However, the exact mechanism that justifies this increased survival is unknown. This study aims to analyze overall survival in elderly patients who have suffered a non-pathological VCF, its causes, and the relationship with different factors. Methods: All patients over 65 years old diagnosed with acute, non-pathologic thoracic or lumbar VCF, treated consecutively in our center from January 2017 to December 2020, were retrospectively selected for analysis. Those patients with follow-ups under two years or who required arthrodesis due to poor fracture evolution were excluded. Only the first process was considered for patients who presented a second VCF in the first three months. Results: A total of 509 consecutive fractures were registered. Seventeen were excluded, leaving 492 cases for final analysis. The mean age was 78.9 years old. Overall mortality was 36.2%. Survival rate at 1-, 12-, 24-, 48-, and 60-month follow-up was 97.4%, 86.6%, 78.0%, 64.4%, and 59.4%, respectively. The independent factors associated with a higher mortality risk were age, male, oncologic history, non-traumatic mechanism, and co-morbidity during hospitalization. No statistical differences were found when comparing the two survival curves by treatment (vertebral augmentation vs. conservative management) over time. No benefit was observed in those patients with comprehensive outpatient geriatric care.  Conclusion: Age, male sex, history of oncological disease, non-traumatic mechanism of the fracture, and any comorbidity during hospitalization were identified as variables independently associated with a higher risk of mortality following a VCF in the elderly. Vertebral augmentation and comprehensive outpatient geriatric care showed no benefit in overall survival.

opencc-zeroApr 2023View details →

Capture histories of owls with covariates for survival analysis

Early life experiences have carry-over effects that manifest in later life stages. Challenging rearing environments result in more energy invested in immediate survival and less energy on growth and maturation, which can decrease survival in both the short and long term. One way to measure differences in energy allocation to growth between individuals is through physiological indices, such as concentrations of the metabolic hormone corticosterone, and body condition. Corticosterone increases in response to challenges to homeostasis and mobilizes stored fat and muscle to meet energetic demands. Maintaining elevated corticosterone can result in poor body condition and decreased survival. Juvenile or pre-breeding age classes are typically a substantial portion of the total population and serve key functions in population dynamics in many long-lived species. Thus, understanding how the rearing environment may influence demographics across life-history stages is crucial to understanding larger population dynamics. Yet, demographic models and conservation planning often lack vital rate estimates for early life stages because, prior to breeding, animals cannot be effectively sampled (i.e., they are unobservable). We used corticosterone concentrations in feathers and body mass of fledged juvenile Northern Spotted Owls (Strix occidentalis caurina) as indicators of potential energetic limitations early in life and used a multi-state modeling framework to quantify the effect of these indicators on apparent annual survival prior to claiming a territory (pre-territorial birds) and the probability of recruiting into the territorial population. Apparent annual survival for pre-territorial birds was higher for birds with greater mass, earlier banding dates, and intermediate levels of corticosterone. Birds with greater mass at banding were also more likely to recruit into the territorial population. Our results demonstrate the importance of early development and traditionally excluded life-history stages on long-term demographics. Although early life stages are difficult to observe, monitoring and conservation efforts may be improved by increasing studies on pre-territorial animals, control of Barred Owls, and conservation of forest structures important for Spotted Owls. This may contribute to increased juvenile survival and recruitment.

ClinicalTrials.gov36/100

Retrospective Multicenter Study of Patient-level T1CE/FLAIR MRI Deep Learning to Predict EGFR/ALK Driver Status in NSCLC Brain Metastases With External Validation and Survival Analysis

ClinicalTrials.gov study NCT07373951. IPD Sharing: UNDECIDED. Countries: 1. Publications: 4.

restrictedIPD-UNDECIDEDFeb 2026View details →

publicNov 2024View details →

Data from: Winners and losers from climate change: An analysis of tree growth and survival responses to temperature and precipitation for roughly 150 species across the contiguous U.S.

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