Seasonal adjustment of time series observed at mixed frequencies using singular value decomposition with wavelet thresholding by Shiyuan He (11282556)

“…Using both simulated and real data, we find that (i) when the seasonality is moderate or strong our proposed method performs well and correctly detects the underlying seasonality structure; and (ii) for single frequency time series, the performance of our proposed method compares well with those of the traditional X-12-ARIMA and SEATS methods, especially in the case when the seasonality is strong.…”

Table 1_A dual-modality machine learning precision diagnostic model integrated radiomics and proteomics for breast cancer.docx by Pengping Li (3574424)

“…A dual-modal diagnostic model was constructed in combination with machine learning algorithms.</p>Results<p>The results showed that the protein marker detection model performed outstandingly in the primary screening of healthy people and breast diseases (with the highest AUC of 0.974). …”

Uncertainty and Novelty in Machine Learning by Derek Scott Prijatelj (20364288)

“…</p> <p>We explore the practical evaluation of novelty detection and adaptation with new benchmarks in handwriting recognition and human activity recognition.…”

Supporting files for thesis "Deep-learning-based Morphological Modelling: Case Study in Soft Robot Control, Shape Sensing and Deformation" by Yingqi Li (9151304)

“…The cost-effective optical waveguide is utilized to detect the light loss induced by surface deformation. …”

Cringe - Emotional manipulation as a tool of political control in Albanian digital campaigns (2025) by Edlira Gugu (21793610)

“…Machine learning algorithms used for sentiment analysis and bot detection. …”

Processed InShaPe dataset: Large-scale multi-shape phase retrieval dataset for PBF-LB/M laser beam shaping SLM phase mask estimation. by Shengyuan Yan (22248700)

“…Codes for optical simulation, deep learning models training and testing, and the simulation-assisted analysis of aberration detection and beam shape correction accuracies for PBF-LB/M systems. …”

Image 1_High incidence and poor prognosis of bone metastases in functioning small intestinal neuroendocrine tumors.jpeg by Annie Mathew (14419053)

“…Whether adapting NET treatment algorithm for BM improves OS needs to be tested in clinical trials.…”

A ballistocardiogram dataset with reference ECG signals for bedside heart rhythm assessment by Jiafeng Qiu (20961312)

“…This dataset comes with synchronized Holter monitor recordings, may advance BCG's utilization in cardiac rhythm assessment and early cardiovascular disease detection, and test the generalizability of BCG algorithms in real-world scenarios with various health conditions.…”

Robust principal component analysis combined with top-hat transform for clutter suppression in GPR images by Fang Ye (112854)

“…The experimental results on simulation and real data show that the proposed method has better performance than several state-of-the-art clutter suppression algorithms.…”

Table 1_Strategies for bridge maintenance using BIM: an analysis of methodologies and tools.xlsx by Emilio Medrano-Sanchez (22449763)

“…Specifically, LiDAR and photogrammetry enabled sub-centimetre models; Convolutional Neural Networks (CNN) and You Only Look Once (YOLO) algorithms reached mean average precision up to 0.91 for crack detection. …”

Supplementary file 1_Machine learning for improved size estimation of complex marine particles from noisy holographic images.docx by Zonghua Liu (155371)

“…Our results show that the proposed strategy of training the model on synthetic and real holographic data improves the model’s performance on edge detection in holographic images. …”

Dataset for Partial Parallelism Plot Analysis in Neurodegeneration Biomarker Assays (2010–2024) by Axel Petzold (7076261)

“…<br></p><p dir="ltr">Each dataset entry is annotated with:</p><ul><li>Sample type (serum, plasma, cerebrospinal fluid)</li><li>Assay platform and dilution steps</li><li>Classification of outcome (partial parallelism achieved or not)</li></ul><p dir="ltr"><b>Use cases:</b><br>This dataset is designed to help researchers, assay developers, and meta-analysts to:</p><ul><li>Reproduce figures and analyses from the published review</li><li>Benchmark or validate new assay performance pipelines</li><li>Train algorithms for automated detection of dilutional non-parallelism</li></ul><p dir="ltr"><b>Files included:</b></p><ul><li><code>.csv</code> files containing dilution–response data</li><li>Metadata spreadsheets with assay and sample annotations</li></ul><p></p>…”

Table 2_Deeper insight into speech characteristics of patients at ultra-high risk using classification and explainability models.xlsx by Deok-Hee Kim-Dufor (21547235)

“…The Synthetic Minority Oversampling Technique was used to handle imbalanced data, and the SHapley Additive exPlanations (SHAP) values were computed to measure feature importance and each feature’s contributions to the classification.…”

Table 1_Deeper insight into speech characteristics of patients at ultra-high risk using classification and explainability models.xlsx by Deok-Hee Kim-Dufor (21547235)

“…The Synthetic Minority Oversampling Technique was used to handle imbalanced data, and the SHapley Additive exPlanations (SHAP) values were computed to measure feature importance and each feature’s contributions to the classification.…”

Supplementary file 1_Machine learning identifies immune-perinatal predictors of infantile hemangioma.xlsx by Dongdong Wu (824557)

“…Comprehensive perinatal, clinical, and laboratory data were collected. Candidate risk factors were identified using logistic regression. …”

Supplementary file 1_A risk prediction system for depression in middle-aged and older adults grounded in machine learning and visualization technology: a cohort study.docx by Jinsong Du (8634642)

“…</p>Methods<p>Using cohort data from the China Health and Retirement Longitudinal Study (CHARLS), involving 8,839 middle-aged and older adult participants, the study developed predictive models based on eight machine learning algorithms, primarily including LightGBM, XGBoost, and AdaBoost. …”

Supplementary file 2_Machine learning identifies immune-perinatal predictors of infantile hemangioma.xlsx by Dongdong Wu (824557)

“…Comprehensive perinatal, clinical, and laboratory data were collected. Candidate risk factors were identified using logistic regression. …”

Stronger Together: Unleashing the Social Impact of Hate Speech Research by Sidney Wong (13714252)

“…S. (2024). Hate speech detection in social media: Techniques, recent trends, and future challenges. …”

Enhancing the Robustness of Vehicle Re-Identification in Intelligent Transportation Systems by Mei Qiu (21081170)

“…</p><p><br></p><p dir="ltr">We developed a comprehensive data set generation pipeline that uses vehicle detection algorithms with confidence scores to select optimal Regions of Interest (ROI) for image cropping. …”

Image 2_A machine learning model to predict neurological deterioration after mild traumatic brain injury in older adults.jpeg by Daisu Abe (20498225)

“…</p>Methods<p>This was a retrospective cohort study of data from the Think FAST registry, a multicenter prospective observational study of elderly TBI patients in Japan. …”