Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
470
datasets available to search
ShareScore release 0.9.0
Dataset results
470 results for “Evaluation dataset”
Dataset - "Performance evaluation of the 3D-ring Cadmium-Zinc-Telluride (CZT) StarGuide system according to the NEMA NU-1 2018 standard"
Open the record for dataset details and reuse information.
Dataset related to article: "Smart Flow for the evaluation of the hemodialysis arteriovenous fistula"
<p>We provide the raw data used for the following article:</p> <ul> <li>Colucci M, Torreggiani M, Bernardi I, Stangalino S, Catucci D, Esposito V, Sileno G, Esposito C.<br> <em>Smart Flow for the evaluation of the hemodialysis arteriovenous fistula</em>. "J Vasc Access". 2020 Sep;21(5):652-657.<br> doi: 10.1177/1129729819897171. Epub 2020 Jan 2. PMID: 31894718.</li> </ul> <p><br> <strong>Background: </strong>Smart Flow is an innovative tool available on the Carestream Touch Prime Ultrasound machines, which provides automated blood flow measurement and shows the vectors that form the blood flow in the vessel. We compared the use of Smart Flow with traditional Duplex Doppler Ultrasound to evaluate blood flow of arteriovenous fistulas in prevalent hemodialysis patients. <strong>Methods: </strong>A total of 31 chronic patients on hemodialysis were enrolled. Blood flow was measured on the brachial artery with Smart Flow and duplex Doppler ultrasound. In a subset of 26 patients, a video of the juxta-anastomotic efferent vein was recorded and analyzed to calculate an index of flow turbulence.<br> <strong>Results:</strong> We enrolled 21 males and 10 females aged 68.52±11.64 years at the time of evaluation with an average arteriovenous fistulas vintage of 50.23±47.42 months and followed them up for 18.03±5.18 months. Smart Flow and Duplex Doppler Ultrasound blood flow measurements positively correlated (p<0.0001) in the same patient but Smart Flow gave higher blood flow values (995.0 vs 730.3mL/min, p<0.0001), and the Duplex Doppler Ultrasound blood flow standard deviation was similar to Smart Flow (125.4 vs 114.4mL/min, p<0.0001). The time needed to evaluate arteriovenous fistulas with Smart Flow was significantly shorter than Duplex Doppler Ultrasound (67.58±19.89 vs 146.3±26.35 s, p<0.0001). No correlation was found between blood flow turbulence and the subsequent access failure.<br> <strong>Conclusion:</strong> Smart Flow is reliable, reproducible, and faster than traditional duplex ultrasound. However, the additional information given by the Smart Flow technique does not seem to add any further benefits in terms of prediction of the access failure</p>
Dataset related to the article: Salvioni E, Mapelli M, Bonomi A, Magri D, Piepoli M, Frigerio M, et al. Pick Your Threshold: A Comparison Among Different Methods of Anaerobic Threshold Evaluation in Heart Failure Prognostic Assessment. Chest. 2022;162:1106-1115.
<p><strong>Background: </strong>In clinical practice, anaerobic threshold (AT) is used to guide training and rehabilitation programs, to define risk of major thoracic or abdominal surgery, and to assess prognosis in heart failure (HF). AT of oxygen uptake (V.O<sub>2</sub>; V.O<sub>2</sub>AT) has been reported as an absolute value (V.O<sub>2</sub>ATabs), as a percentage of predicted peak V.O<sub>2</sub> (V.O<sub>2</sub>AT%peak_pred), or as a percentage of observed peak V.O<sub>2</sub> (V.O<sub>2</sub>AT%peak_obs). A direct comparison of the prognostic power among these different ways to report AT is missing.</p> <p><strong>Research question: </strong>What is the prognostic power of these different ways to report AT?</p> <p><strong>Study design and methods: </strong>In this observational cohort study, we screened data of 7,746 patients with HF with a history of reduced ejection fraction (< 40%) recruited between 1998 and 2020 and enrolled in the Metabolic Exercise Combined With Cardiac and Kidney Indexes register. All patients underwent a maximum cardiopulmonary exercise test, executed using a ramp protocol on an electronically braked cycle ergometer.</p> <p><strong>Results: </strong>This study considered 6,157 patients with HF with identified AT. Follow-up was median, 4.2 years (25th-75th percentiles, 1.9-5.0 years). Both V.O<sub>2</sub>ATabs (mean ± SD, 823 ± 305 mL/min) and V.O<sub>2</sub>AT%peak_pred (mean ± SD, 39.6 ± 13.9%), but not V.O<sub>2</sub>AT%peak_obs (mean ± SD, 69.2 ± 17.7%), well stratified the population regarding prognosis (composite end point: cardiovascular death, urgent heart transplant, or left ventricular assist device). Comparing area under the receiver operating characteristic curve (AUC) values, V.O<sub>2</sub>ATabs (0.680) and V.O<sub>2</sub>AT%peak_pred (0.688) performed similarly, whereas V.O<sub>2</sub>AT%peak_obs (0.538) was significantly weaker (P < .001). Moreover, the V.O<sub>2</sub>AT%peak_pred AUC value was the only one performing as well as the AUC based on peak V.O<sub>2</sub> (0.710), with an even a higher AUC (0.637 vs 0.618, respectively) in the group with severe HF (peak V.O<sub>2</sub> < 12 mL/min/kg). Finally, the combination of V.O<sub>2</sub>AT%peak_pred with peak V.O<sub>2</sub> and V. per CO<sub>2</sub> production shows the highest prognostic power.</p> <p><strong>Interpretation: </strong>In HF, V.O<sub>2</sub>AT%peak_pred is the best way to report V.O<sub>2</sub> at AT in relationship to prognosis, with a prognostic power comparable to that of peak V.O<sub>2</sub> and, remarkably, in patients with severe HF.</p>
Dataset related to article "Endoscopic ultrasound-guided fine-needle biopsy with or without macroscopic on-site evaluation: a randomized controlled noninferiority trial "
<p>This record contains raw data related to article “Endoscopic ultrasound-guided fine-needle biopsy with or without macroscopic on-site evaluation: a randomized controlled noninferiority trial"</p> <p>Abstract</p> <p>BACKGROUND : The advantage of using the macroscopic on-site evaluation (MOSE) technique during endoscopic ultrasound-guided fine-needle biopsy (EUS-FNB) performed with 22G Franseen needles has not been investigated. We aimed to compare EUS-FNB with MOSE vs. EUS-FNB performed with three needle passes. METHODS : This randomized trial involved 10 Italian referral centers. Consecutive patients referred for EUS-FNB of pancreatic or nonpancreatic solid lesions were included in the study and randomized to the two groups. MOSE was performed by gross visualization of the collected material by the endoscopists and considered adequate when a white/yellowish aggregate core longer than 10 mm was retrieved. The primary outcome was diagnostic accuracy. Secondary outcomes were specimen adequacy, number of needle passes, and safety. RESULTS : 370 patients with 234 pancreatic lesions (63.2 %) and 136 nonpancreatic lesions (36.8 %) were randomized (190 EUS-FNB with MOSE and 180 with standard EUS-FNB). No statistically significant differences were found between EUS-FNB with MOSE and conventional EUS-FNB in terms of diagnostic accuracy (90.0 % [95 %CI 84.8 %-93.9 %] vs. 87.8 % [95 %CI 82.1 %-92.2 %]; <em>P</em> = 0.49), sample adequacy (93.1 % [95 %CI 88.6 %-96.3 %] vs. 95.5 % [95 %CI 91.4 %-98 %]; <em>P</em> = 0.31), and rate of adverse events (2.6 % vs. 1.1 %; <em>P</em> = 0.28). The median number of passes was significantly lower in the EUS-FNB with MOSE group (1 vs. 3; <em>P</em> < 0.001). CONCLUSIONS : The accuracy of EUS-FNB with MOSE is noninferior to that of EUS-FNB with three needle passes. MOSE reliably assesses sample adequacy and reduces the number of needle passes required to obtain the diagnosis with a 22G Franseen needle.</p>
Dataset related to the article "AI-SCoRE (artificial intelligence-SARS CoV2 risk evaluation): a fast, objective and fully automated platform to predict the outcome in COVID-19 patients"
<p>This record contains partial raw data related to the article “AI-SCoRE (artificial intelligence-SARS CoV2 risk evaluation): a fast, objective and fully automated platform to predict the outcome in COVID-19 patients”</p> <p><strong>Purpose: </strong>To develop and validate an effective and user-friendly AI platform based on a few unbiased clinical variables integrated with advanced CT automatic analysis for COVID-19 patients' risk stratification.</p> <p><strong>Material and methods: </strong>In total, 1575 consecutive COVID-19 adults admitted to 16 hospitals during wave 1 (February 16-April 29, 2020), submitted to chest CT within 72 h from admission, were retrospectively enrolled. In total, 107 variables were initially collected; 64 extracted from CT. The outcome was survival. A rigorous AI model selection framework was adopted for models selection and automatic CT data extraction. Model performances were compared in terms of AUC. A web-mobile interface was developed using Microsoft PowerApps environment. The platform was externally validated on 213 COVID-19 adults prospectively enrolled during wave 2 (October 14-December 31, 2020).</p> <p><strong>Results: </strong>The final cohort included 1125 patients (292 non-survivors, 26%) and 24 variables. Logistic showed the best performance on the complete set of variables (AUC = 0.839 ± 0.009) as in models including a limited set of 13 and 5 variables (AUC = 0.840 ± 0.0093 and AUC = 0.834 ± 0.007). For non-inferior performance, the 5 variables model (age, sex, saturation, well-aerated lung parenchyma and cardiothoracic vascular calcium) was selected as the final model and the extraction of CT-derived parameters was fully automatized. The fully automatic model showed AUC = 0.842 (95% CI: 0.816-0.867) on wave 1 and was used to build a 0-100 scale risk score (AI-SCoRE). The predictive performance was confirmed on wave 2 (AUC 0.808; 95% CI: 0.7402-0.8766).</p> <p><strong>Conclusions: </strong>AI-SCoRE is an effective and reliable platform for automatic risk stratification of COVID-19 patients based on a few unbiased clinical data and CT automatic analysis.</p>
Dataset related to "Evaluation of iron overload in nigrosome 1 via quantitative susceptibility mapping as a progression biomarker in prodromal stages of synucleinopathies"
<p>Data supporting the journal article:</p> <p>Lancione, Marta, et al. "Evaluation of iron overload in nigrosome 1 via quantitative susceptibility mapping as a progression biomarker in prodromal stages of synucleinopathies." <em>NeuroImage</em> 260 (2022): 119454.</p>
Dataset relate to article "TOWARDS A NEW ASSESSMENT TOOL FOR CAREGIVERS OF PATIENTS WITH DISORDERS OF CONSCIOUSNESS: THE SOCIAL AND FAMILY EVALUATION SCALE (SAFE)"
<p>FOR EVERY PARTICIPANT, THE RESPONSE AT EACH QUESTION OF THE SURVEY IS PROVIDED.</p>
Dataset related to article "Multicentric evaluation of a machine learning model to streamline the radiotherapy patient specific quality assurance process"
<p> This record contains raw data related to article “Multicentric evaluation of a machine learning model to streamline the radiotherapy patient specific quality assurance process"</p> <p><em>Purpose:</em> Patient-specific quality assurance (PSQA) is performed to ensure that modulated treatment plans can be delivered as intended, but constitutes a substantial workload that could slow down the radiotherapy process and delay the start of clinical treatments. In this study, we investigated a machine learning (ML) tree-based ensemble model to predict the gamma passing rate (GPR) for volumetric modulated arc therapy (VMAT) plans.</p> <p><em>Materials and Methods:</em> 5622 VMAT plans from multiple treatment sites were selected from a database of Institution 1 and the ML model trained using 19 metrics. PSQA analyses were performed automatically using criteria 3%/1 mm (global normalization, absolute dose, 10% threshold) and 95% action limit. Model’s performance was evaluated on an out-of-sample test set of Institution 1 and on two independent sets of measurements collected at Institution 2 and Institution 3. Mean absolute error (MAE), as well as the model’s sensitivity and specificity, were computed.</p> <p><em>Results:</em> The model obtained a MAE of 2.33%, 2.54% and 3.91% for the three Institutions, with a specificity of 0.90, 0.90 and 0.68, and a sensitivity of 0.61, 0.25, and 0.55, respectively. Small positive median values of the residuals (i.e., the difference between measurements and predictions) were observed for each Institution (0.95%, 1.66%, and 3.42%). Thus, the model’s predictions were, on average, close to the real values and provided a conservative estimation of the GPR.</p> <p><em>Conclusions</em>: ML models can be integrated into clinical practice to streamline the radiotherapy workflow, but they should be center-specific or thoroughly verified within centers before clinical use.</p> <p> </p>
ZooScan77: ZooScan zooplankton image dataset for Migratory Crossroads ML/DL model training and evaluation
<h2><em>ZooScan77</em></h2> <p>This dataset contains a collection of ca. 1,000,000 images of 77 zooplankton, micronekton and detritus categories captured by ZooScan imager. The dataset is <strong>not</strong> <strong>public</strong> and must <strong>only</strong> be used within the scope of Migratory Crossroads project only. </p>
Dataset_A Psychometric Tool for Evaluating Executive Functions in Parkinson's Disease
<p>Dataset of raw data used in the paper "A Psychometric Tool for Evaluating Executive Functions in Parkinson’s Disease"</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.