Image 2_Functional and clinical validation of tsRNA-defined molecular subtypes guides precision therapy in gastric cancer.tif by Ye Tian (220278)

“…A prognostic model was constructed using machine learning algorithms and validated across multiple cohorts. The functional role of a key tsRNA, tsRNA-Asp-3-0024, was investigated through Pandora-seq, qRT-PCR, and in vitro and organoid-based assays.…”

Image 5_Functional and clinical validation of tsRNA-defined molecular subtypes guides precision therapy in gastric cancer.tif by Ye Tian (220278)

“…A prognostic model was constructed using machine learning algorithms and validated across multiple cohorts. The functional role of a key tsRNA, tsRNA-Asp-3-0024, was investigated through Pandora-seq, qRT-PCR, and in vitro and organoid-based assays.…”

PCA of full simulated repertoire using sequence descriptors. by Katharina Waury (14203284)

Table 1_Ensemble machine learning for predicting renal function decline in chronic kidney disease: development and external validation.docx by Hong Chen (108084)

“…Introduction<p>Chronic kidney disease (CKD) poses a significant global health challenge, requiring timely interventions to manage renal function decline. Traditional predictive models often lack accuracy and generalizability. …”

Antibody pair dataset characteristics. by Katharina Waury (14203284)

Uncertainty Based Machine Learning-DFT Hybrid Framework for Accelerating Geometry Optimization by Akksay Singh (20176616)

“…Compared to previous active learning approaches, our algorithm adds two key features: a modified delta method incorporating force information to enhance efficiency in uncertainty estimation, and a quasi-Newton approach based upon a Hessian matrix calculated from the neural network; the later improving stability of optimization near critical points. …”

Data Sheet 1_Multi-omics analysis and metastasis risk factor prediction in N1b stage PTMC: insights into immune infiltration and therapeutic implications.docx by Hao Dai (4277254)

Table 1_Diagnostic performance of artificial intelligence in detecting oral potentially malignant disorders and oral cancer using medical diagnostic imaging: a systematic review an... by Rakesh Kumar Sahoo (12420508)

“…While visual examination is the primary method for detecting oral cancer, it may not be practical in remote areas. AI algorithms have shown some promise in detecting cancer from medical images, but their effectiveness in oral cancer detection remains Naïve. …”

Predicted F1 score across temporal aggregation levels and BirdNET parameters. by Andrew J. Fairbairn (22231970)

S1 Graphical abstract - by José M. Rivera-Arbeláez (12418512)

“…The tissues’ contractile force, one of the main hallmarks of tissue function and maturation level of cardiomyocytes, can be read out from EHT platforms by optically tracking the movement of elastic pillars induced by the contractile tissues. …”

Data Sheet 1_Flow-based parameterization for DAG and feature discovery in scientific multimodal data.pdf by Elise Walker (19937997)

“…<p>Representation learning algorithms are often used to extract essential features from high-dimensional datasets. …”

Data Sheet 4_Identification of a signature gene set for oxaliplatin sensitivity prediction in colorectal cancer.pdf by Xiaopeng Zhan (4170574)

“…Machine learning algorithms to these datasets was applied to identify genes associated with oxaliplatin response. …”

Data Sheet 1_Identification of a signature gene set for oxaliplatin sensitivity prediction in colorectal cancer.pdf by Xiaopeng Zhan (4170574)

“…Machine learning algorithms to these datasets was applied to identify genes associated with oxaliplatin response. …”

Table 1_Identification of a signature gene set for oxaliplatin sensitivity prediction in colorectal cancer.xlsx by Xiaopeng Zhan (4170574)

“…Machine learning algorithms to these datasets was applied to identify genes associated with oxaliplatin response. …”

Data Sheet 2_Identification of a signature gene set for oxaliplatin sensitivity prediction in colorectal cancer.pdf by Xiaopeng Zhan (4170574)

“…Machine learning algorithms to these datasets was applied to identify genes associated with oxaliplatin response. …”

Image 1_Identification of a signature gene set for oxaliplatin sensitivity prediction in colorectal cancer.pdf by Xiaopeng Zhan (4170574)

“…Machine learning algorithms to these datasets was applied to identify genes associated with oxaliplatin response. …”

Data Sheet 3_Identification of a signature gene set for oxaliplatin sensitivity prediction in colorectal cancer.pdf by Xiaopeng Zhan (4170574)

“…Machine learning algorithms to these datasets was applied to identify genes associated with oxaliplatin response. …”

Antivirus Engines (PowerPoint) by Paul A. Gagniuc (1818325)

“…[EN] The presentation provides a systematic overview of the architecture and functionality of antivirus engines, covering classical detection methods based on signatures as well as advanced techniques involving heuristics, behavioral analysis, and modern innovations in cybersecurity. …”

The research framework. by Shikun Chen (14625352)

“…The approach leverages gradient information from neural networks to guide SLSQP optimization while maintaining XGBoost’s prediction precision. …”

Quantum Chemistry-Guided Machine Learning for Accelerated Design of CO₂‑Solubilizing Deep Eutectic Solvents by Dingkai Hu (16277547)

“…We compiled 2287 experimental measurements from 119 DESs over wide temperature (293.15–353.15 K) and pressure (26.3–7620 kPa) ranges. …”