Image 2_Revealing key regulatory factors in lung adenocarcinoma: the role of epigenetic regulation of autophagy-related genes from transcriptomics, scRNA-seq, and machine learning.... by Xianchang Zeng (9329117)

“…</p>Conclusion<p>In this study, we utilized bulk and single-cell transcriptomic data to uncover the potential molecular mechanisms of A-ERGs in lung cancer. …”

Image 1_Revealing key regulatory factors in lung adenocarcinoma: the role of epigenetic regulation of autophagy-related genes from transcriptomics, scRNA-seq, and machine learning.... by Xianchang Zeng (9329117)

“…</p>Conclusion<p>In this study, we utilized bulk and single-cell transcriptomic data to uncover the potential molecular mechanisms of A-ERGs in lung cancer. …”

Table 1_Assessing the diagnostic value of qPCR for Trichuris trichiura: sub-analysis of a multi-country clinical trial to determine the efficacy of albendazole compared to an alben... by Pedro E. Fleitas (8704023)

“…Additionally, machine learning algorithms were used to predict infection intensity from qPCR Ct-values and demographic variables. qPCR confirmed the superior efficacy of FDC compared to albendazole as previously shown by KK, but discrepancies were observed in CRs between qPCR and KK, particularly lower qPCR CRs for FDC×1 and FDC×3. …”

Presentation 2_Deep learning radiomics nomogram predicts lymph node metastasis in laryngeal squamous cell carcinoma.pptx by Yun Liang (383275)

“…Radiomics features were extracted from CT images, and 7 machine learning algorithms were used to develop 7 radiomics models, which were combined with deep learning features extracted from the ResNet50 deep learning network to form deep learning radiomics (DLR) models. …”

Image 1_Safety assessment of temozolomidee: real-world adverse event analysis from the FAERS database.png by Yu Liu (6938)

“…Background<p>Temozolomidee (TMZ) is an alkylating antitumor drug used in the treatment of glioblastoma and anaplastic astrocytoma. …”

Table 1_Identification and validation of CKAP2 as a novel biomarker in the development and progression of rheumatoid arthritis.docx by Qiongbing Zheng (4741563)

“…Differentially expressed gene (DEG) analysis, functional enrichment analysis, and weighted gene co-expression network analysis (WGCNA) identified key gene modules in RA. Machine learning algorithms were used to identify hub genes, followed by immune infiltration analysis and gene set variation analysis (GSVA). …”

Table 1_A novel muscle network approach for objective assessment and profiling of bulbar involvement in ALS.docx by Panying Rong (2697181)

“…This tool has various strengths, including the use of a clinically readily available noninvasive instrument, fully automated data processing and analytics, and generation of interpretable objective outcome measures (i.e., latent factors), together rendering it highly scalable in routine clinical practice for assessing and monitoring of bulbar involvement.…”

Table 2_A real−world pharmacovigilance study of FDA Adverse Event Reporting System events for pralsetinib.xlsx by Yi Yin (448434)

“…</p>Conclusion<p>Our pharmacovigilance analysis of real-world data from the FEARS database revealed the safety signals and potential risks of pralsetinib usage. …”

Table 3_A real−world pharmacovigilance study of FDA Adverse Event Reporting System events for pralsetinib.xlsx by Yi Yin (448434)

“…</p>Conclusion<p>Our pharmacovigilance analysis of real-world data from the FEARS database revealed the safety signals and potential risks of pralsetinib usage. …”

Table 1_A real−world pharmacovigilance study of FDA Adverse Event Reporting System events for pralsetinib.docx by Yi Yin (448434)

“…</p>Conclusion<p>Our pharmacovigilance analysis of real-world data from the FEARS database revealed the safety signals and potential risks of pralsetinib usage. …”

Pipeline for preterm birth classifier construction. by Zhiwei Guo (335819)

“…The whole-genome sequencing data was then used to develop classifiers for predicting PTB via a three-step process: discovery, training, and validation. …”

<b>Neural Symbolic Vault: Symbolic Species and</b> <b>DNA Co-Encoding Research Bundle v1.0 (A+M[S] Archive)</b> by Jeffrey Siergiej (20937434)

“…<p dir="ltr">License Type:</p><p dir="ltr">Custom Siergiej Services IPNX License – Non-transferable, non-commercial use only unless otherwise contracted. See included LICENSE.txt for terms.…”

AP-2α 相关研究 by Ya-Hong Wang (21080642)

“…Pathogenicity of the wild-type, VdAP-2α mutant, and complemented strain on cotton seedlings. (A) Disease phenotypes and longitudinal sections of cotton stems infected with the wild-type, VdAP-2α mutant, and complemented strains. …”

Genosophus: A Dynamical-Systems Diagnostic Engine for Neural Representation Analysis by Alan Glanz (22109698)

“…</p><h2><b>Intended Applications</b></h2><ul><li>Diagnosis of representational collapse or instability</li><li>Detection of emergent structure in transformers</li><li>Monitoring internal geometry during training or RLHF</li><li>Studying drift and novelty in sequential reasoning tasks</li><li>Complementing mechanistic interpretability efforts</li><li>Model evaluation and safety diagnostics</li></ul><h2><b>Intellectual Property Notice</b></h2><p dir="ltr">This diagnostic framework and its algorithmic components are covered under a U.S. …”