Table 2_SZBC-AI4TCM: a comprehensive web-based computing platform for traditional Chinese medicine research and development.xlsx by Jidong Lang (802830)

“…</p>Methods<p>We developed a comprehensive web-based computing platform, SZBC-AI4TCM, a comprehensive web-based computing platform for traditional Chinese medicine that embodies the “ShuZhiBenCao” (Digital Herbal) concept through artificial intelligence, designed to accelerate TCM research and reduce costs by integrating advanced AI algorithms and bioinformatics tools.</p>Results<p>Leveraging machine learning, deep learning, and big data analytics, the platform enables end-to-end analysis, from TCM formulation and mechanism elucidation to drug screening. …”

Table 1_Metabolome profiling by untargeted metabolomics and biomarker panel selection using machine-learning for patients in different stages of peripheral neuropathy induced by ox... by Yu-jiao Hua (22274131)

“…At the same time, our findings implied that the occurrence of OIPN may be associated with the progression of the disease and the patients’ tumor markers (CEA, CA19-9, CA72-4), as well as immune response and inflammation (ANC, PLT), and metabolic and liver function abnormalities (GGT and UA) (P<0.05).Multivariate statistical analysis combined with SHAP-guided machine learning identified six biomarkers, including thiabendazole, 1-methylxanthine, imidazol-5-yl-pyruvate, 5-hydroxypentanoic acid, spermidine, and 4’-oxolividamine that consistently distinguished OIPN patients (Level 1-3) from non-OIPN controls (Level 0). …”

Image 4_Metabolome profiling by untargeted metabolomics and biomarker panel selection using machine-learning for patients in different stages of peripheral neuropathy induced by ox... by Yu-jiao Hua (22274131)

“…At the same time, our findings implied that the occurrence of OIPN may be associated with the progression of the disease and the patients’ tumor markers (CEA, CA19-9, CA72-4), as well as immune response and inflammation (ANC, PLT), and metabolic and liver function abnormalities (GGT and UA) (P<0.05).Multivariate statistical analysis combined with SHAP-guided machine learning identified six biomarkers, including thiabendazole, 1-methylxanthine, imidazol-5-yl-pyruvate, 5-hydroxypentanoic acid, spermidine, and 4’-oxolividamine that consistently distinguished OIPN patients (Level 1-3) from non-OIPN controls (Level 0). …”

Supplementary file 2_Professional content analysis and quality assessment of cardiopulmonary resuscitation educational videos on social media platforms: a comparative study of YouT... by Chuanliang Pan (21650213)

“…Background<p>Cardiopulmonary resuscitation (CPR) is an emergency medical procedure designed to restore circulation and respiratory function in patients who have suffered cardiac arrest. …”

Image 3_Metabolome profiling by untargeted metabolomics and biomarker panel selection using machine-learning for patients in different stages of peripheral neuropathy induced by ox... by Yu-jiao Hua (22274131)

“…At the same time, our findings implied that the occurrence of OIPN may be associated with the progression of the disease and the patients’ tumor markers (CEA, CA19-9, CA72-4), as well as immune response and inflammation (ANC, PLT), and metabolic and liver function abnormalities (GGT and UA) (P<0.05).Multivariate statistical analysis combined with SHAP-guided machine learning identified six biomarkers, including thiabendazole, 1-methylxanthine, imidazol-5-yl-pyruvate, 5-hydroxypentanoic acid, spermidine, and 4’-oxolividamine that consistently distinguished OIPN patients (Level 1-3) from non-OIPN controls (Level 0). …”

Table 3_SZBC-AI4TCM: a comprehensive web-based computing platform for traditional Chinese medicine research and development.xlsx by Jidong Lang (802830)

“…</p>Methods<p>We developed a comprehensive web-based computing platform, SZBC-AI4TCM, a comprehensive web-based computing platform for traditional Chinese medicine that embodies the “ShuZhiBenCao” (Digital Herbal) concept through artificial intelligence, designed to accelerate TCM research and reduce costs by integrating advanced AI algorithms and bioinformatics tools.</p>Results<p>Leveraging machine learning, deep learning, and big data analytics, the platform enables end-to-end analysis, from TCM formulation and mechanism elucidation to drug screening. …”

Table 3_Metabolome profiling by untargeted metabolomics and biomarker panel selection using machine-learning for patients in different stages of peripheral neuropathy induced by ox... by Yu-jiao Hua (22274131)

“…At the same time, our findings implied that the occurrence of OIPN may be associated with the progression of the disease and the patients’ tumor markers (CEA, CA19-9, CA72-4), as well as immune response and inflammation (ANC, PLT), and metabolic and liver function abnormalities (GGT and UA) (P<0.05).Multivariate statistical analysis combined with SHAP-guided machine learning identified six biomarkers, including thiabendazole, 1-methylxanthine, imidazol-5-yl-pyruvate, 5-hydroxypentanoic acid, spermidine, and 4’-oxolividamine that consistently distinguished OIPN patients (Level 1-3) from non-OIPN controls (Level 0). …”

Table6_Analysis of immunogenic cell death in periodontitis based on scRNA-seq and bulk RNA-seq data.xlsx by Erli Wu (17785482)

“…Subsequently, consensus clustering analysis was performed to identify ICD-associated subtypes, and multiple bioinformatics algorithms were used to investigate differences in immune cells and pathways between subtypes. …”

Table5_Analysis of immunogenic cell death in periodontitis based on scRNA-seq and bulk RNA-seq data.xlsx by Erli Wu (17785482)

“…Subsequently, consensus clustering analysis was performed to identify ICD-associated subtypes, and multiple bioinformatics algorithms were used to investigate differences in immune cells and pathways between subtypes. …”

Image 5_Metabolome profiling by untargeted metabolomics and biomarker panel selection using machine-learning for patients in different stages of peripheral neuropathy induced by ox... by Yu-jiao Hua (22274131)

“…At the same time, our findings implied that the occurrence of OIPN may be associated with the progression of the disease and the patients’ tumor markers (CEA, CA19-9, CA72-4), as well as immune response and inflammation (ANC, PLT), and metabolic and liver function abnormalities (GGT and UA) (P<0.05).Multivariate statistical analysis combined with SHAP-guided machine learning identified six biomarkers, including thiabendazole, 1-methylxanthine, imidazol-5-yl-pyruvate, 5-hydroxypentanoic acid, spermidine, and 4’-oxolividamine that consistently distinguished OIPN patients (Level 1-3) from non-OIPN controls (Level 0). …”

Table2_Analysis of immunogenic cell death in periodontitis based on scRNA-seq and bulk RNA-seq data.docx by Erli Wu (17785482)

“…Subsequently, consensus clustering analysis was performed to identify ICD-associated subtypes, and multiple bioinformatics algorithms were used to investigate differences in immune cells and pathways between subtypes. …”

Data Sheet 1_Comparison of clinical nasal endoscopy, optical biopsy, and artificial intelligence in early diagnosis and treatment planning in laryngeal cancer: a prospective observ... by Ruifang Hu (21515339)

“…Prompt diagnosis is crucial to improving survival and function. Direct laryngoscopy and imaging modalities are conventional diagnostic methods. …”

Image 1_Metabolome profiling by untargeted metabolomics and biomarker panel selection using machine-learning for patients in different stages of peripheral neuropathy induced by ox... by Yu-jiao Hua (22274131)

“…At the same time, our findings implied that the occurrence of OIPN may be associated with the progression of the disease and the patients’ tumor markers (CEA, CA19-9, CA72-4), as well as immune response and inflammation (ANC, PLT), and metabolic and liver function abnormalities (GGT and UA) (P<0.05).Multivariate statistical analysis combined with SHAP-guided machine learning identified six biomarkers, including thiabendazole, 1-methylxanthine, imidazol-5-yl-pyruvate, 5-hydroxypentanoic acid, spermidine, and 4’-oxolividamine that consistently distinguished OIPN patients (Level 1-3) from non-OIPN controls (Level 0). …”

Table1_Analysis of immunogenic cell death in periodontitis based on scRNA-seq and bulk RNA-seq data.docx by Erli Wu (17785482)

“…Subsequently, consensus clustering analysis was performed to identify ICD-associated subtypes, and multiple bioinformatics algorithms were used to investigate differences in immune cells and pathways between subtypes. …”

Table 1_SZBC-AI4TCM: a comprehensive web-based computing platform for traditional Chinese medicine research and development.xlsx by Jidong Lang (802830)

“…</p>Methods<p>We developed a comprehensive web-based computing platform, SZBC-AI4TCM, a comprehensive web-based computing platform for traditional Chinese medicine that embodies the “ShuZhiBenCao” (Digital Herbal) concept through artificial intelligence, designed to accelerate TCM research and reduce costs by integrating advanced AI algorithms and bioinformatics tools.</p>Results<p>Leveraging machine learning, deep learning, and big data analytics, the platform enables end-to-end analysis, from TCM formulation and mechanism elucidation to drug screening. …”

Table 2_Metabolome profiling by untargeted metabolomics and biomarker panel selection using machine-learning for patients in different stages of peripheral neuropathy induced by ox... by Yu-jiao Hua (22274131)

“…At the same time, our findings implied that the occurrence of OIPN may be associated with the progression of the disease and the patients’ tumor markers (CEA, CA19-9, CA72-4), as well as immune response and inflammation (ANC, PLT), and metabolic and liver function abnormalities (GGT and UA) (P<0.05).Multivariate statistical analysis combined with SHAP-guided machine learning identified six biomarkers, including thiabendazole, 1-methylxanthine, imidazol-5-yl-pyruvate, 5-hydroxypentanoic acid, spermidine, and 4’-oxolividamine that consistently distinguished OIPN patients (Level 1-3) from non-OIPN controls (Level 0). …”

Table4_Analysis of immunogenic cell death in periodontitis based on scRNA-seq and bulk RNA-seq data.xlsx by Erli Wu (17785482)

“…Subsequently, consensus clustering analysis was performed to identify ICD-associated subtypes, and multiple bioinformatics algorithms were used to investigate differences in immune cells and pathways between subtypes. …”

Table3_Analysis of immunogenic cell death in periodontitis based on scRNA-seq and bulk RNA-seq data.xlsx by Erli Wu (17785482)

“…Subsequently, consensus clustering analysis was performed to identify ICD-associated subtypes, and multiple bioinformatics algorithms were used to investigate differences in immune cells and pathways between subtypes. …”

Table 1_Explainable machine learning prediction of internet addiction among Chinese primary and middle school children and adolescents: a longitudinal study based on positive youth... by Jiahe Liu (9096353)

“…Our study aimed to examine the risk factors associated with IA among Chinese children and adolescents and leverage explainable machine learning (ML) algorithms to predict IA status at the time of assessment, based on Young’s Internet Addiction Test.…”

DataSheet1_Extrachromosomal circular DNAs in prostate adenocarcinoma: global characterizations and a novel prediction model.PDF by Qingliu He (12528332)

“…The immune microenvironment of the risk model was quantified using a variety of immunological algorithms, which also identified its characteristics with regard to immunotherapy, immune response, and immune infiltration.…”