Pipeline of the interactor algorithm. by Jose Cleydson F. Silva (8685594)

Number of offspring as a function of the number of mismatches for the best couple (blue) and the second-best couple (red) found by APIS parentage assignment. by Julien Roche (611898)

A) Ranking of models trained on different feature sets across all tested algorithms, sorted by their F1-score. by Jose Cleydson F. Silva (8685594)

The real NGD values, one-step ahead training set predictions, and multi-step ahead test set predictions using the AI-AFTER algorithm for Kayseri. by Burak Alakent (463512)

Differential expression analysis of the NAFLD and AIS datasets. by Junjie Su (368807)

Isologs, function and residue information of 12 key proteins in MPV replication. by Huaichuan Duan (6458477)

Synthetic Realness: Authenticity as Algorithm (Reality Drift Working Paper Series, 2025) by Reality Drift Working Papers Series 2020-2025 (22445446)

GeoUrbNet: A Multi-Source Graph-Based Framework and Dataset for Urban Building Function Analysis by haoyue Jiao (21411491)

Supplementary file 1_Predicting the onset of internalizing disorders in early adolescence using deep learning optimized with AI.zip by Nina de Lacy (6559520)

Data Sheet 1_AI-enabled workforce integration: blended human resource contribution rate in Chinese companies.pdf by Kexin Zhang (301752)

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)

“…</p>Conclusion<p>These findings suggest that AI algorithms have the potential to function as reliable tools for the early diagnosis of OPMDs and oral cancer, offering significant advantages, particularly in resource-constrained settings.…”

IOWarp v1.0 Beta: Advancing Scientific AI with Intelligent Data Management & MCP Integration by Anthony Kougkas (17069216)

Screening of the potential small-molecular compounds for the treatment of NAFLD and AIS by cMAP analysis. by Junjie Su (368807)

Data Sheet 1_Understanding acceptance and resistance toward generative AI technologies: a multi-theoretical framework integrating functional, risk, and sociolegal factors.docx by Priyanka Shrivastava (472059)

“…Additionally, the manuscript now highlights demographic diversity, including variations in age, gender, and academic discipline, as relevant to AI adoption patterns. Ethical concerns, including algorithmic bias, data ownership, and the labor market impact of AI, are addressed to offer a more holistic understanding of resistance behavior. …”

Drug Release Nanoparticle System Design: Data Set Compilation and Machine Learning Modeling by Shan He (121220)

Subjects:

Functional module diagram. by Fan Hongxia (21029673)

“…The intelligent system supports visual, intelligent, and scientific water-saving management, offering essential data and functional tools for urban water-using units. Future efforts should focus on further utilizing big data and artificial intelligence algorithms to simulate and identify water use characteristics, so as to assess the unreasonable water usage more scientifically and provide more effective support for water conservation work.…”

Exponentially attenuated sinusoidal function. by Hang Zhao (143592)

“…<div><p>Recent research for arrhythmia classification is increasingly based on AI-driven approaches, which are primarily grounded in ECG data, but often neglect the mathematical foundations of cardiac electrophysiology. …”

AI-Assisted Label-Free Monitoring Bone Mineral Metabolism on Demineralized Bone Paper by Patrick Ryan (532054)

“…Here, we present a label-free, longitudinal, and quantitative monitoring of mineralized collagen formation by osteoblasts and subsequent osteoclast-driven mineral resorption on DBP using brightfield microscopy. A Segment.ai machine learning algorithm is applied for time-lapse bright-field image analysis, enabling identification of osteoclast resorption areas and automated quantification of large image datasets over a three-week culture period. …”

AI-Assisted Label-Free Monitoring Bone Mineral Metabolism on Demineralized Bone Paper by Patrick Ryan (532054)

“…Here, we present a label-free, longitudinal, and quantitative monitoring of mineralized collagen formation by osteoblasts and subsequent osteoclast-driven mineral resorption on DBP using brightfield microscopy. A Segment.ai machine learning algorithm is applied for time-lapse bright-field image analysis, enabling identification of osteoclast resorption areas and automated quantification of large image datasets over a three-week culture period. …”

AI-Assisted Label-Free Monitoring Bone Mineral Metabolism on Demineralized Bone Paper by Patrick Ryan (532054)

“…Here, we present a label-free, longitudinal, and quantitative monitoring of mineralized collagen formation by osteoblasts and subsequent osteoclast-driven mineral resorption on DBP using brightfield microscopy. A Segment.ai machine learning algorithm is applied for time-lapse bright-field image analysis, enabling identification of osteoclast resorption areas and automated quantification of large image datasets over a three-week culture period. …”