Table 5_Explainable machine learning reveals ribosome biogenesis biomarkers in preeclampsia risk prediction.xlsx by Jingjing Chen (293564)

“…</p>Methods<p>We integrated placental transcriptomic data from two datasets (GSE75010, GSE10588) to systematically investigate ribosome biogenesis dysregulation in preeclampsia. Functional enrichment analyses delineated the dysregulation of pathways, while weighted gene co-expression network analysis identified hub genes within ribosome biogenesis-associated modules. …”

Table 2_Explainable machine learning reveals ribosome biogenesis biomarkers in preeclampsia risk prediction.xlsx by Jingjing Chen (293564)

“…</p>Methods<p>We integrated placental transcriptomic data from two datasets (GSE75010, GSE10588) to systematically investigate ribosome biogenesis dysregulation in preeclampsia. Functional enrichment analyses delineated the dysregulation of pathways, while weighted gene co-expression network analysis identified hub genes within ribosome biogenesis-associated modules. …”

Table 3_Explainable machine learning reveals ribosome biogenesis biomarkers in preeclampsia risk prediction.xlsx by Jingjing Chen (293564)

“…</p>Methods<p>We integrated placental transcriptomic data from two datasets (GSE75010, GSE10588) to systematically investigate ribosome biogenesis dysregulation in preeclampsia. Functional enrichment analyses delineated the dysregulation of pathways, while weighted gene co-expression network analysis identified hub genes within ribosome biogenesis-associated modules. …”

Data Sheet 1_Explainable machine learning reveals ribosome biogenesis biomarkers in preeclampsia risk prediction.docx by Jingjing Chen (293564)

“…</p>Methods<p>We integrated placental transcriptomic data from two datasets (GSE75010, GSE10588) to systematically investigate ribosome biogenesis dysregulation in preeclampsia. Functional enrichment analyses delineated the dysregulation of pathways, while weighted gene co-expression network analysis identified hub genes within ribosome biogenesis-associated modules. …”

Data Sheet 1_Investigating neural markers of Alzheimer's disease in posttraumatic stress disorder using machine learning algorithms and magnetic resonance imaging.pdf by Gabriella Yakemow (20137758)

“…The objective of this study was to identify structural and functional neural changes in patients with PTSD that may contribute to the future development of AD.…”

Video 1_Development and control of a robotic assistant walking aid for fall risk reduction.mp4 by Marcel Naderer (22434454)

“…To enable effective and reliable control in the real system, actuator dynamics are characterized through an optimization-based system identification approach, resulting in transfer function models with over 98% accuracy. Based on these models, PID controllers are optimally tuned using an optimization algorithm to ensure fast and accurate corrective action. …”

Pearson correlation coefficient for this specific 10 second subset is 0.61, though the whole 12 min recording scores a 0.50. by Nicholas A. Rondoni (21573261)

Visualization of approximations by Nicholas A. Rondoni (21573261)

Median fiber cleavage time (black) and the fraction of successful runs (red) for different parameter values. by Roukayatou R. Ouedraogo (20460980)

This figure shows a non-exhaustive representation of the main models reported in our discussion, for illustrative purpose only. by Giuseppe Agapito (104634)

Osseointegration of an innovative functionally gradient biomimetic scaffold based on Voronoi-Tessellation for the design of orthopaedic implants by Yuzhu Wang (845659)

Data Sheet 1_Simplified two-compartment neuron with calcium dynamics capturing brain-state specific apical-amplification, -isolation and -drive.pdf by Elena Pastorelli (7024235)

“…A machine learning evolutionary algorithm, guided by a set of fitness functions, selected parameters defining neurons that express the desired apical dendritic mechanisms. …”

Spatial characterization of cancer-associated cell types in human breast cancer malignancies. by Nuray Sogunmez Erdogan (21533872)

<b>A Multi-Pathology Ballistocardiogram Dataset for Cardiac Function Monitoring and Arrhythmia Assessment</b> by Jing Zhan (20716673)

“…<p dir="ltr">This dataset comprises 153 subfolders within a primary directory named <i>data</i>, derived from 85 participants. …”

Precise spatial delineation of brain cell types in adult mouse brain. by Nuray Sogunmez Erdogan (21533872)

Deconvolution challenges due to coherence and heterogeneity. by Nuray Sogunmez Erdogan (21533872)

Optimal progressively censored reliability sampling plans for log-location-scale distributions by Chien-Tai Lin (22673615)

“…<p>Here, we introduce a variable neighborhood search algorithm-based approach to determine the minimum sample sizes required for progressively censored reliability sampling plans within the flexible family of log-location-scale family of distributions, which includes Weibull and log-logistic distributions. …”

Data Sheet 1_A novel approach to monitoring rehabilitation progress in atrophic muscle using contactless measurement of free oscillations and advanced modal analysis.pdf by Agnieszka Tomaszewska (2022379)

Diagrammatic sketch of railway grid. by Liying Wang (288626)

“…These expressions are determined using the copula function, and an algorithm is designed to construct the corresponding transition probability matrix. …”

Parameters of the Gamma increment processes. by Liying Wang (288626)

“…These expressions are determined using the copula function, and an algorithm is designed to construct the corresponding transition probability matrix. …”