Variable analysis using conventional statistics. by Ana Torres (8919335)

“…This approach could prove instrumental to train future supervised algorithms based on larger patient cohorts both for a more precise diagnosis and to gain insight into fundamental aspects of this complication of visceral leishmaniasis.…”

Table 1_Drug-induced agranulocytosis: a disproportionality analysis and umbrella review.docx by Yajie Lu (8367015)

“…This study aimed to provide the current overview of DIA for clinical guidance.</p>Methods<p>Using real-world data from FDA Adverse Event Reporting System (FAERS), we performed a disproportionality analysis to identify the drugs associated with agranulocytosis, employing the information component and reporting odds ratio algorithms. …”

Table 3_DEPDC1B, CDCA2, APOBEC3B, and TYMS are potential hub genes and therapeutic targets for diagnosing dialysis patients with heart failure.xlsx by Wenwu Tang (5493086)

“…However, there is still a lack of effective and reliable HF diagnostic markers and therapeutic targets for patients with MHD.</p>Methods<p>In this study, we analyzed transcriptome profiles of 30 patients with MHD by high-throughput sequencing. …”

Table 5_DEPDC1B, CDCA2, APOBEC3B, and TYMS are potential hub genes and therapeutic targets for diagnosing dialysis patients with heart failure.xlsx by Wenwu Tang (5493086)

“…However, there is still a lack of effective and reliable HF diagnostic markers and therapeutic targets for patients with MHD.</p>Methods<p>In this study, we analyzed transcriptome profiles of 30 patients with MHD by high-throughput sequencing. …”

Table 2_Drug-induced agranulocytosis: a disproportionality analysis and umbrella review.docx by Yajie Lu (8367015)

“…This study aimed to provide the current overview of DIA for clinical guidance.</p>Methods<p>Using real-world data from FDA Adverse Event Reporting System (FAERS), we performed a disproportionality analysis to identify the drugs associated with agranulocytosis, employing the information component and reporting odds ratio algorithms. …”

Abbreviations used in the text. by Lorenzo Ruinelli (13014138)

“…Machine Learning (ML) algorithms were developed with 10-fold cross-validation, and diagnostic accuracy was evaluated.…”

Variables defining worsening PKDL. by Ana Torres (8919335)

“…This approach could prove instrumental to train future supervised algorithms based on larger patient cohorts both for a more precise diagnosis and to gain insight into fundamental aspects of this complication of visceral leishmaniasis.…”

Data Sheet 1_Quality, reliability, and dissemination of lung cancer information on short-video platforms in China: a cross-platform content analysis of TikTok, Kwai, and Rednote.do... by Xiaoran Zheng (6254537)

“…Professional, evidence-based content enhances reliability, whereas emotional and visually driven content drives engagement. …”

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

“…A total of 95 significant disproportionality preferred terms (PTs) conformed to the four algorithms simultaneously. AEs that ranked the top three at the PT level were hypertension (n = 80), asthenia (n = 79), and anemia (n = 65). …”

Table 1_Integrated transcriptomics and machine learning reveal REN as a dual regulator of tumor stemness and NK cell evasion in Wilms tumor progression.xlsx by Qingfei Cao (12062217)

“…A novel Cancer Stemness Prognostic Index (CSPI) was developed using machine learning algorithms to stratify WT patients by risk and histological subtype. …”

CANDID-II Dataset by Sijing Feng (10187216)

“…This dataset can be used for training and testing for deep learning algorithms for adult chest x rays.</p><p dir="ltr">Unfortunately, since Feb 2024, the New Zealand government is changing the data governance on datasets used for AI development and this affects the process of how the CANDID II dataset is to be accessed by the external users. …”

Table 2_Artificial intelligence in vaccine research and development: an umbrella review.docx by Rabie Adel El Arab (14113425)

“…Nonetheless, persistent challenges emerged—data heterogeneity, algorithmic bias, limited regulatory frameworks, and ethical concerns over transparency and equity.…”

Table 3_Artificial intelligence in vaccine research and development: an umbrella review.docx by Rabie Adel El Arab (14113425)

“…Nonetheless, persistent challenges emerged—data heterogeneity, algorithmic bias, limited regulatory frameworks, and ethical concerns over transparency and equity.…”

Table 1_Artificial intelligence in vaccine research and development: an umbrella review.docx by Rabie Adel El Arab (14113425)

“…Nonetheless, persistent challenges emerged—data heterogeneity, algorithmic bias, limited regulatory frameworks, and ethical concerns over transparency and equity.…”

Data Sheet 1_Multi-omics derivation of a core gene signature for predicting therapeutic response and characterizing immune dysregulation in inflammatory bowel disease.csv by Mingming Wang (394106)

“…Current precision medicine approaches lack robust molecular tools integrating transcriptomic signatures with immune dynamics for personalized treatment guidance.</p>Methods<p>We performed multi-omics analyses of GEO datasets using machine learning algorithms (LASSO/Random Forest) to derive a four-gene signature. …”

Image 1_Multi-omics derivation of a core gene signature for predicting therapeutic response and characterizing immune dysregulation in inflammatory bowel disease.jpeg by Mingming Wang (394106)

“…Current precision medicine approaches lack robust molecular tools integrating transcriptomic signatures with immune dynamics for personalized treatment guidance.</p>Methods<p>We performed multi-omics analyses of GEO datasets using machine learning algorithms (LASSO/Random Forest) to derive a four-gene signature. …”

Table 1_Plasma exosomal lncRNA-related signatures define molecular subtypes and predict survival and treatment response in hepatocellular carcinoma.docx by Fangmin Zhong (17415318)

“…</p>Methods<p>The transcriptomic data from 230 plasma exosomes and 831 HCC tissues were integrated. …”

CANDID-III Dataset by Sijing Feng (10187216)

“…This dataset can be used for training and testing for deep learning algorithms for adult chest x rays.</p><p dir="ltr">Unfortunately, since Feb 2024, the New Zealand government is changing the data governance on datasets used for AI development and this affects the process of how the CANDID III dataset is to be accessed by the external users. …”

Image 13_Immune intrinsic escape signature stratifies prognosis, characterizes the tumor immune microenvironment, and identifies tumorigenic PPP1R8 in glioblastoma multiforme patie... by Ran Du (552530)

“…</p>Conclusion<p>The IERGs-based signature offers reliable prognostication for GBM, validated across multiple datasets. …”

Image 1_Polyamine metabolism related gene index prediction of prognosis and immunotherapy response in breast cancer.jpeg by Ruoya Wang (842048)

“…This study aimed to determine whether polyamine metabolism-related genes (PMRGs) could predict prognosis and immunotherapy efficacy in Breast Cancer (BC).</p>Methods<p>We conducted a comprehensive multi-omics analysis of PMRG expression profiles in BC. …”