External cohort raw data. حسب Lei Gao (6566)

"…</p><p>However, no predictive models for BSH have been developed using machine learning algorithms.</p><p>Objective</p><p>To evaluate the effectiveness of five machine learning algorithms in predicting thickening of the basal segment of the interventricular septum and to develop a simple, yet efficient, prediction model for BSH.…"

Internal cohort raw data. حسب Lei Gao (6566)

"…</p><p>However, no predictive models for BSH have been developed using machine learning algorithms.</p><p>Objective</p><p>To evaluate the effectiveness of five machine learning algorithms in predicting thickening of the basal segment of the interventricular septum and to develop a simple, yet efficient, prediction model for BSH.…"

Test set quantitative segmentation performance summary. The upper half of the table shows the performance of the network when trained using CT images as input while the bottom half... حسب Alex J. Allphin (17102503)

الموضوعات:

Quantile Regression and Homogeneity Identification of a Semiparametric Panel Data Model حسب Rui Li (4631)

"…To this end, we propose a homogeneity identification algorithm based on binary segmentation. For the determination of the thresholding parameter in homogeneity identification, we propose a generalized Bayesian information criterion. …"

The image represents the results of passing the first slice of the Kasthuri++ testing data through trained M1 and M2 models to obtain their respective predicted outputs. حسب Yubraj Gupta (7465394)

الموضوعات:

Topographic map of the Central China. The filled red triangles represent the lightning sensors within the domain. Elevation data obtained from NASA's Shuttle Radar Topography Missi... حسب Manxing Shi (22367181)

الموضوعات:

Similar to Fig 10, but for 0100–0400 BJT (Beijing Time) on 17 July 2015. حسب Manxing Shi (22367181)

الموضوعات:

Similar to Fig 7, but for the year 2014. حسب Manxing Shi (22367181)

الموضوعات:

A multi-scale spatiotemporal neighborhood-based approach for identifying lightning clusters. حسب Manxing Shi (22367181)

الموضوعات:

Workflow for determining adaptive clustering parameters. حسب Manxing Shi (22367181)

الموضوعات:

Similar to Fig 7, but for the year 2015. حسب Manxing Shi (22367181)

الموضوعات:

Monthly counts of lightning strokes and grid clusters and the proportion of grid clusters with more than 500 strokes during 2013–2015. حسب Manxing Shi (22367181)

الموضوعات:

Fine-scale identification results of lightning clusters in the study area during 2013–2015 using adaptive-parameter spatiotemporal clustering (CSCAP) and fixed-parameter spatiotemp... حسب Manxing Shi (22367181)

الموضوعات:

Hierarchical relationships among key terms used in this study. حسب Manxing Shi (22367181)

الموضوعات:

Statistical properties of high-flash-rate (≥500 lightning strokes) grid clusters identified in 2013 within the study region: (A) Spatial distribution of cluster centroids; (B, C) P... حسب Manxing Shi (22367181)

الموضوعات:

Preprocessing and segmentation of H&E-stained breast tumor tissue images. حسب Chen Chen (6544)

Comparison of infant and model data. حسب Johanna K. Theuer (19942849)

Data Sheet 1_Instance segmentation models for detecting floating macroplastic debris from river surface images.pdf حسب Tomoya Kataoka (6758831)

Data Sheet 2_Deep learning for MRI-based acute and subacute ischaemic stroke lesion segmentation—a systematic review, meta-analysis, and pilot evaluation of key results.docx حسب Makram Baaklini (21515348)

"…We systematically reviewed the literature (2015–2023) for deep learning algorithms that segment acute and/or subacute stroke lesions on brain MRI seeking to address this question, meta-analysed the data extracted, and evaluated the results.…"

Data Sheet 1_Deep learning for MRI-based acute and subacute ischaemic stroke lesion segmentation—a systematic review, meta-analysis, and pilot evaluation of key results.docx حسب Makram Baaklini (21515348)

"…We systematically reviewed the literature (2015–2023) for deep learning algorithms that segment acute and/or subacute stroke lesions on brain MRI seeking to address this question, meta-analysed the data extracted, and evaluated the results.…"