<b>Engineered </b><b>VPg</b><b> </b><b>saRNA achieves cap-independent,</b><b> </b><b>low-immunogenic and precise</b><b> </b><b>encoding of therapeutic proteins </b><b>in vivo</b><b... by Zunyong feng (22673801)

“…Source parameters included a source temperature of 120 °C, desolvation temperature of 300 °C, and cone voltages of 25 V (reference) and 20 V (sample). Raw spectra were processed and deconvoluted using MassLynx 4.1 with the MaxEnt1 Transform algorithm to obtain zero-charge intact molecular masses. …”

Presentation 1_Circulating biomarkers associated with pediatric sickle cell disease.pptx by Cecilia Elorm Lekpor (20453195)

“…We conclude that a predictive algorithm based on these biomarkers could be developed and validated through longitudinal assessment of within-genotype differences and correlation of the data with disease severity or outcomes. …”

Fig 2 - by Elizabeth Ajalo (19234898)

“…<div><p>Background</p><p>Chat Generative Pre-trained Transformer (ChatGPT) is a 175-billion-parameter natural language processing model that uses deep learning algorithms trained on vast amounts of data to generate human-like texts such as essays. …”

Characteristics of the participants. by Elizabeth Ajalo (19234898)

“…<div><p>Background</p><p>Chat Generative Pre-trained Transformer (ChatGPT) is a 175-billion-parameter natural language processing model that uses deep learning algorithms trained on vast amounts of data to generate human-like texts such as essays. …”

Fig 1 - by Elizabeth Ajalo (19234898)

“…<div><p>Background</p><p>Chat Generative Pre-trained Transformer (ChatGPT) is a 175-billion-parameter natural language processing model that uses deep learning algorithms trained on vast amounts of data to generate human-like texts such as essays. …”

Fig 3 - by Elizabeth Ajalo (19234898)

“…<div><p>Background</p><p>Chat Generative Pre-trained Transformer (ChatGPT) is a 175-billion-parameter natural language processing model that uses deep learning algorithms trained on vast amounts of data to generate human-like texts such as essays. …”

GridScopeRodents: High-Resolution Global Typical Rodents Distribution Projections from 2021 to 2100 under Diverse SSP-RCP Scenarios by Yang Lan (20927512)

“…The dataset is publicly available via Figshare for Institutions (UCL).</p><p dir="ltr">All data are stored in GeoTIFF (.tif) format and can be accessed and processed using ArcGIS, ENVI, R, and Python. …”

Table 1_Correlation of triglyceride-glucose index with the incidence and prognosis of hyperglycemic crises in critically ill patients with diabetes mellitus: a machine-learning-bas... by Mingchen Xie (4325692)

“…This study aims to evaluate the relationship between the TyG index and HCE incidence/clinical outcomes in critically ill patients with DM and to construct a risk prediction model using machine-learning algorithms.</p>Methods<p>This multi-center retrospective investigation leveraged clinical repositories from Medical Information Mart for Intensive Care IV (MIMIC-IV) and eICU Collaborative Research Database (eICU-CRD). …”

JDS_Supplementary_Tables_Touil_et_al._Reticuloruminal_pH_and_Subacute_Ruminal_Acidosis_prediction.pdf by Tesnime Touil (19066216)

“…Additionally, different ML algorithms, including partial least squares (PLS), random forest (RF), and gradient boosting (GB), were used to predict rpH and SARA. …”

Data Sheet 1_Exploring nonlinear and interaction effects of urban campus built environments on exercise walking using crowdsourced data.csv by Bo Lu (241075)

“…</p>Methods<p>This study utilized crowdsourced exercise walking data and incorporated diverse campus characteristics to construct a multidimensional variable system. …”

Data Sheet 2_Exploring nonlinear and interaction effects of urban campus built environments on exercise walking using crowdsourced data.csv by Bo Lu (241075)

“…</p>Methods<p>This study utilized crowdsourced exercise walking data and incorporated diverse campus characteristics to construct a multidimensional variable system. …”

Using artificial intelligence in the development of diagnostic models of coronary artery disease based on ECG features: A scoping review by Rong Yang (21661040)

“…</p><p dir="ltr">Extracted Fields:</p><table><tr><td><p dir="ltr">​​Category​​</p></td><td><p dir="ltr">​​Variables​​</p></td></tr><tr><td><p dir="ltr">Study Metadata​​</p></td><td><p dir="ltr">Authors, year, country, design, objectives</p></td></tr><tr><td><p dir="ltr">Population & Data Source​​</p></td><td><p dir="ltr">Cohort characteristics (age, sex), database (e.g., PTB-XL), sample size</p></td></tr><tr><td><p dir="ltr">AI Model Details​​</p></td><td><p dir="ltr">Algorithm (e.g., 1D-CNN, SVM), ECG features (e.g., QTc, spectral entropy)</p></td></tr><tr><td><p dir="ltr">Performance & Validation​​</p></td><td><p dir="ltr">Metrics (Acc, Sens, Spec), validation method (internal/external), generalizability</p></td></tr><tr><td><p dir="ltr">Critical Appraisal​​</p></td><td><p dir="ltr">Clinical relevance, limitations, implementation barriers</p></td></tr></table><p dir="ltr">7. …”

Figure 3 from Chromothripsis-Mediated Small Cell Lung Carcinoma by Natasha Rekhtman (15014156)

“…<b>B,</b> CN log ratio plots from the FACETS algorithm displaying the distinctive oscillating CN states on chromosomes with chromothripsis. …”

Table 1_Development of an alkaliptosis-related lncRNA risk model and immunotherapy target analysis in lung adenocarcinoma.docx by Xiang Xiong (1810234)

“…</p>Methods<p>The TCGA database was utilized to obtain RNA-seq-based transcriptome profiling data, clinical information, and mutation data. We conducted multivariate Cox regression analysis to identify alkaliptosis-related lncRNAs. …”

<b>Dataset of GPi Deep Brain Stimulation in a Hemi-Parkinsonian rat model</b> by Mohammad Mehdi Ostad Ali Akbary (20848154)

“…Every .mat file stores the positional data of the rat’s head and back from a 30-second video recording.…”

<b>Responsible Artificial Intelligence (RAI) Measures Dataset</b> by Shalaleh Rismani (21704225)

“…</p><ol><li>Measure</li><li>Measurement Process</li></ol><p dir="ltr"><b>Entry Points (Columns C and D in Orange)</b>: The primary features in narrowing down potential measures for an algorithmic system.…”

Genomic determinants in pathogenicity of SARS-CoV-2 versa common cold coronaviruses by Zahra Arab-Bafrani (20309630)

“…These remarkable oligonucleotides might point toward the existence of some particular RNA elements that might be involved in viral virulence and thus can be targeted for viral treatment in the future.…”

VIIDA and InViDe: computational approaches for generating and evaluating inclusive image paragraphs for the visually impaired by Daniel L. Fernandes (20416673)

“…<p>Existing image description methods when used as Assistive Technologies often fall short in meeting the needs of blind or low vision (BLV) individuals. …”

Image 1_Transcriptomic insights into the mechanism of action of telomere-related biomarkers in rheumatoid arthritis.tif by Lijuan Feng (3746086)

“…Biomarkers were subsequently identified using machine learning algorithms, receiver operating characteristic analysis, and expression level comparisons between RA and control samples. …”

Table 9_Transcriptomic insights into the mechanism of action of telomere-related biomarkers in rheumatoid arthritis.xlsx by Lijuan Feng (3746086)

“…Biomarkers were subsequently identified using machine learning algorithms, receiver operating characteristic analysis, and expression level comparisons between RA and control samples. …”