DataSheet1_Late-life suicide: machine learning predictors from a large European longitudinal cohort.docx by Nicola Meda (19530745)

“…We matched 73 individuals who died by suicide with people who died by accident, according to sex (28.8% female in the total sample), age at death (67 ± 16.4 years), suicidal ideation (measured with the EURO-D scale), and the number of chronic illnesses. A random forest algorithm was trained on demographic data, physical health, depression, and cognitive functioning to extract essential variables for predicting death from suicide and then tested on the test set.…”

Gradient Porous Flexible Pressure Sensors with the Relay Effect for High-Accuracy Braille-to-Speech Recognition by Xiaoyu Zhang (62901)

“…However, traditional flexible pressure sensors often suffer from limited compressibility in their structural design, resulting in rapid saturation of the detection range and low sensitivity, which hinder their commercial viability. …”

Image 1_Exploring the role of mitochondrial metabolism and immune infiltration in myocardial infarction: novel insights from bioinformatics and experimental validation.tif by Jingyi Hou (698975)

“…Experimental validation of hub mitoDEGs, immune cell markers (F4/80, CD163 and CD86), and apoptosis-related proteins (BAX/BCL-2 and cleaved caspase-3) was conducted in MI mice, and the association with cardiac function was explored.…”

Data Sheet 1_The potential of ME1 in guiding immunotherapeutic strategies for ovarian cancer: insights from pan-cancer research.docx by Jiahui Wei (8289561)

“…Additionally, we examined the correlation between ME1 expression and several factors, including methylation status, tumor mutation burden (TMB), microsatellite instability (MSI), immune regulator genes, immune checkpoints, tumor microenvironment scores, functional enrichment, single-cell analysis, and drug sensitivity. …”

Accelerating Fock Build via Hybrid Analytical-Numerical Integration by Yong Zhang (5893)

“…To distinguish from the original COSX algorithm (which does not involve the partition of the density matrix <b>D</b>), we denote the presently revised variant as COSx. …”

Accelerating Fock Build via Hybrid Analytical-Numerical Integration by Yong Zhang (5893)

“…To distinguish from the original COSX algorithm (which does not involve the partition of the density matrix <b>D</b>), we denote the presently revised variant as COSx. …”

Supplementary file 1_Integrating bioinformatics and molecular experiments to reveal the critical role of the cellular energy metabolism-related marker PLA2G1B in COPD epithelial ce... by Jun Shi (289433)

“…</p>Material and methods<p>This research identified cell energy metabolism-related differentially expressed genes (CEM-DEGs) by collecting CEM-associated signatures from multiple public databases and integrating these markers with data from the GEO database. …”

Image 4_Machine learning-based diagnostic and prognostic models for breast cancer: a new frontier on the clinical application of natural killer cell-related gene signatures in prec... by Yutong Fang (16621143)

“…We constructed ML-based diagnostic models using 12 algorithms and evaluated their performance for identifying the optimal ML diagnostic model. …”

Image 8_Machine learning-based diagnostic and prognostic models for breast cancer: a new frontier on the clinical application of natural killer cell-related gene signatures in prec... by Yutong Fang (16621143)

“…We constructed ML-based diagnostic models using 12 algorithms and evaluated their performance for identifying the optimal ML diagnostic model. …”

Table 1_Machine learning-based diagnostic and prognostic models for breast cancer: a new frontier on the clinical application of natural killer cell-related gene signatures in prec... by Yutong Fang (16621143)

“…We constructed ML-based diagnostic models using 12 algorithms and evaluated their performance for identifying the optimal ML diagnostic model. …”

Image 3_Machine learning-based diagnostic and prognostic models for breast cancer: a new frontier on the clinical application of natural killer cell-related gene signatures in prec... by Yutong Fang (16621143)

“…We constructed ML-based diagnostic models using 12 algorithms and evaluated their performance for identifying the optimal ML diagnostic model. …”

Image 9_Machine learning-based diagnostic and prognostic models for breast cancer: a new frontier on the clinical application of natural killer cell-related gene signatures in prec... by Yutong Fang (16621143)

“…We constructed ML-based diagnostic models using 12 algorithms and evaluated their performance for identifying the optimal ML diagnostic model. …”

Image 6_Machine learning-based diagnostic and prognostic models for breast cancer: a new frontier on the clinical application of natural killer cell-related gene signatures in prec... by Yutong Fang (16621143)

“…We constructed ML-based diagnostic models using 12 algorithms and evaluated their performance for identifying the optimal ML diagnostic model. …”

Image 5_Machine learning-based diagnostic and prognostic models for breast cancer: a new frontier on the clinical application of natural killer cell-related gene signatures in prec... by Yutong Fang (16621143)

“…We constructed ML-based diagnostic models using 12 algorithms and evaluated their performance for identifying the optimal ML diagnostic model. …”

Table 2_Machine learning-based diagnostic and prognostic models for breast cancer: a new frontier on the clinical application of natural killer cell-related gene signatures in prec... by Yutong Fang (16621143)

“…We constructed ML-based diagnostic models using 12 algorithms and evaluated their performance for identifying the optimal ML diagnostic model. …”

Image 10_Machine learning-based diagnostic and prognostic models for breast cancer: a new frontier on the clinical application of natural killer cell-related gene signatures in pre... by Yutong Fang (16621143)

“…We constructed ML-based diagnostic models using 12 algorithms and evaluated their performance for identifying the optimal ML diagnostic model. …”

Image 2_Machine learning-based diagnostic and prognostic models for breast cancer: a new frontier on the clinical application of natural killer cell-related gene signatures in prec... by Yutong Fang (16621143)

“…We constructed ML-based diagnostic models using 12 algorithms and evaluated their performance for identifying the optimal ML diagnostic model. …”

Image 7_Machine learning-based diagnostic and prognostic models for breast cancer: a new frontier on the clinical application of natural killer cell-related gene signatures in prec... by Yutong Fang (16621143)

“…We constructed ML-based diagnostic models using 12 algorithms and evaluated their performance for identifying the optimal ML diagnostic model. …”

Image 1_Machine learning-based diagnostic and prognostic models for breast cancer: a new frontier on the clinical application of natural killer cell-related gene signatures in prec... by Yutong Fang (16621143)

“…We constructed ML-based diagnostic models using 12 algorithms and evaluated their performance for identifying the optimal ML diagnostic model. …”

Figure 3 from Membrane-bound Heat Shock Protein mHsp70 Is Required for Migration and Invasion of Brain Tumors by Maxim Shevtsov (15023874)

“…<b>C–E,</b> Analysis of the mass spectrometry data from isolated lipid rafts. Protein functional groups identified using the STRING database in the proteome of lipid rafts from three tumor zones (Supplementary Fig. …”