stGRL: spatial domain identification, denoising, and imputation algorithm for spatial transcriptome data based on multi-task graph contrastive representation learning by Xin Lu, Murong Zhou, Bo Gao, Fang Wang, Shuilin Jin, Qiaoming Liu, Guohua Wang

“…However, due to current technical limitations, spatial transcriptomics data often exhibit high dropout rates and noise, posing challenges for downstream analysis, like spot clustering, differential gene analysis, and spatial domain identification. …”
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Superficially Plausible Outputs from a Black Box: Problematising GenAI Tools for Analysing Qualitative SoTL Data by Mirjam Sophia Glessmer, Rachel Forsyth

“… Generative AI tools (GenAI) are increasingly used for academic tasks, including qualitative data analysis for the Scholarship of Teaching and Learning (SoTL). …”
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Research on the Cultivation of Practical English Talents Based on a Big Data-Driven Model and Sentiment Dictionary Analysis by Qiuwei Fang

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Prediction of retention time in larger antisense oligonucleotide datasets using machine learning by Manal Rahal, Bestoun S. Ahmed, Christoph A. Bauer, Johan Ulander, Jörgen Samuelsson

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From manual clinical criteria to machine learning algorithms: Comparing outcome endpoints derived from diverse electronic health record data modalities. by Shreya Chappidi, Mason J Belue, Stephanie A Harmon, Sarisha Jagasia, Ying Zhuge, Erdal Tasci, Baris Turkbey, Jatinder Singh, Kevin Camphausen, Andra V Krauze

“…Given emerging research in multi-modal machine learning (ML), we explored the benefits and challenges associated with mining different electronic health record (EHR) data modalities and automating extraction of PFS metrics via ML algorithms.…”
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Enhancing software development effort estimation with a cloud-based data framework using use case points, fuzzy logic, and machine learning by Ritu, Pankaj Bhambri

“…In the end, reports and comparative analysis are generated using a business intelligence tool based on different properties in the repository data.…”
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Long duration multi-channel surface electromyographic signals during walking at natural pace: Data acquisition and analysis. by Francesco Di Nardo, Christian Morbidoni, Grazia Iadarola, Susanna Spinsante, Sandro Fioretti

“…The considerable duration of the signals makes this dataset particularly useful for studies where a significant volume of data is crucial, such as machine/deep learning approaches, investigations examining the variability of muscle recruitment during physiological walking, validations of the reliability of novel sEMG-based algorithms, and assembly of reference datasets for pathological condition characterization.…”
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Evaluation of Pharmaceutical Companies Introduced in Tehran Stock Exchange Using Balanced Scorecard Method and Data Envelopment Analysis by Fatemeh Sadat Aghaei, Majid Annabi

“…The main purpose of this study is to evaluate the efficiency of pharmaceutical companies introduced in the Tehran Stock Exchange based on the model Balanced Scorecard, and using data envelopment analysis. Methods:    In the beginning, performance evaluation indicators from four perspectives: financial, customer, internal processes, and learning and growth; then the efficiency of these companies is considered based on the indicators considered in the model (BSC), measured using (DEA). …”
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Exploring technological evolution of AIED field using topic modelling and link prediction analysis based on patent data by Hüseyin Özçınar, Aylin Sabancı Bayramoğlu

“…This study aims to analyze the artificial intelligence in education (AIED) field using patent data to identify the key actors, main themes, and their evolution over time. …”
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Development and Validation of a Machine Learning Model for Early Prediction of Delirium in Intensive Care Units Using Continuous Physiological Data: Retrospective Study by Chanmin Park, Changho Han, Su Kyeong Jang, Hyungjun Kim, Sora Kim, Byung Hee Kang, Kyoungwon Jung, Dukyong Yoon

“…ObjectiveWe aimed to create a novel machine learning model for delirium prediction in ICU patients using only continuous physiological data. …”
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What are the influential factors for emotional regulation? A latent profile analysis based on PISA 2022 Taiwan data by Edward Hung Cheng Su, Chia Hsin Chen

“…Thus, the aim of the study was to examine the current state of emotional regulation among 15-year-old students in Taiwan using data from PISA 2022 database. First, the study sought to explore different level in emotional regulation across various latent classes through Latent Profile Analysis (LPA). …”
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Assessing urban spatial vitality in post-port areas: a multimodal data analysis of Shanghai, Liverpool, and Marseille by Chen Zeng, Tianchen DAI, Feng Wang, Jiangyue Wu

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Physics-Based and Data-Driven Retrofitting Solutions for Energy Efficiency and Thermal Comfort in the UK: IoT-Validated Analysis by Elena Imani, Huda Dawood, Sean Williams, Nashwan Dawood

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Deep‐Learning Based Causal Inference: A Feasibility Study Based on Three Years of Tectonic‐Climate Data From Moxa Geodynamic Observatory by Wasim Ahmad, Valentin Kasburg, Nina Kukowski, Maha Shadaydeh, Joachim Denzler

“…We propose to use the theoretically well‐established Knockoffs framework to generate in‐distribution, uncorrelated copies of the original data as interventional variables and test the model invariance for causal discovery. …”
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Cluster Analysis of Comparative Genomic Hybridization (CGH) Data Using Self-Organizing Maps: Application to Prostate Carcinomas by Torsten Mattfeldt, Hubertus Wolter, Ralf Kemmerling, Hans‐Werner Gottfried, Hans A. Kestler

“…In this paper we present the application of a self‐organizing map (Genecluster) as a tool for cluster analysis of data from pT2N0 prostate cancer cases studied by CGH. …”
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Power flow analysis and volt/var control strategy of the active distribution network based on data-driven method by Chen Hui, Zhu Weiping, Liu Liguo, Shi Mingming, Xie Wenqiang, Zhang Chenyu

“…Firstly, the CatBoost machine learning model for the distribution network power flow analysis is proposed, and the nonlinear mapping relationship between the distribution network state and power flow results is described from the data-driven perspective. …”
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An explainable web application based on machine learning for predicting fragility fracture in people living with HIV: data from Beijing Ditan Hospital, China by Bo Liu, Bo Liu, Qiang Zhang, Qiang Zhang, Xin Li, Xin Li

“…PurposeThis study aimed to develop and validate a novel web-based calculator using machine learning algorithms to predict fragility fracture risk in People living with HIV (PLWH), who face increased morbidity and mortality from such fractures.MethodWe retrospectively analyzed clinical data from Beijing Ditan Hospital orthopedic department between 2015 and September 2023. …”
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Downscaling and Gap-Filling GRACE-Based Terrestrial Water Storage Anomalies in the Qinghai–Tibet Plateau Using Deep Learning and Multi-Source Data by Jun Chen, Linsong Wang, Chao Chen, Zhenran Peng

“…While the Gravity Recovery and Climate Experiment (GRACE) and its Follow-On (GRACE-FO) missions have revolutionized monitoring of terrestrial water storage anomalies (TWSAs) across this hydrologically sensitive region, spatial resolution limitations (3°, equivalent to ~300 km) constrain process-scale analysis, compounded by mission temporal discontinuity (data gaps). …”
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Domain-weighted transfer learning and discriminative embeddings for low-resource speaker verification by Han Wang, Mingrui He, Mingjun Zhang, Changzhi Luo, Longting Xu

“…Abstract Transfer learning has been shown to be effective in enhancing speaker verification performance in low-resource conditions. …”
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Ensemble Streamflow Simulations in a Qinghai–Tibet Plateau Basin Using a Deep Learning Method with Remote Sensing Precipitation Data as Input by Jinqiang Wang, Zhanjie Li, Ling Zhou, Chi Ma, Wenchao Sun

“…These findings highlight that the proposed 1D CNN ensemble simulation framework has great potential to improve streamflow estimations using remote sensing precipitation data as input and may provide new insight into how deep learning methods advance the application of remote sensing in hydrological research.…”
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