Inherently interpretable deep learning framework highlights clinically relevant image regions. by Kerol Djoumessi (21349992)

Data Sheet 1_Identification of potential biomarkers for lung adenocarcinoma: a study based on bioinformatics analysis combined with validation experiments.zip by Chuchu Zhang (2562154)

“…Background<p>The prognosis for lung adenocarcinoma (LUAD) remains dismal, with a 5-year survival rate of <20%. Therefore, the purpose of this study was to identify potentially reliable biomarkers in LUAD by machine learning combination with Mendelian randomization (MR).…”

<b>Academic procrastination is linked to negative urgency traits: a fMRI resting-state approach</b> by Valeria Cancino (20765381)

Observer model and human/model behavior for two observers. by Sarit F.A. Szpiro (21094755)

“…<p>(A) A population of tuned sensory neurons encodes motion direction (tuning curves representing the mean stimulus response; Before training - light blue, upper panels; After training – dark blue, inverted, lower panels). …”

Aging and affective prosody: A comparative study (Baglione et al., 2025) by Héloïse Baglione (21553577)

Supplementary file 1_Harnessing AI for aphasia: a case report on ChatGPT's role in supporting written expression.docx by Avery K. Allen (21449492)

Embracing GenAI in Engineering Education: Lessons from the Trenches by Lorena A. Barba (97553)

“…Students quickly developed patterns of using AI as a shortcut rather than a learning companion, leading to decreased attendance and an "illusion of competence." …”

Supplementary file 1_SRC is a potential target of Arctigenin in treating triple-negative breast cancer: based on machine learning algorithms, molecular modeling and in Vitro test.d... by Yuezhou Huang (9998177)

“…Western blotting indicated that AG significantly reduced the levels of Bcl-2, caspase-3, and caspase-9, as well as decreased SRC, p-PI3K-p85, p-AKT1, p-MEK1/2, and p-ERK1/2 expression in TNBC cells in a concentration dependent manner.…”

Image 1_Construction of a diagnostic model and identification of effect genes for diabetic kidney disease with concurrent vascular calcification based on bioinformatics and multipl... by Lili Huang (125493)

“…Objective<p>This study aims to construct a diagnostic model for diabetic kidney disease (DKD) with concurrent vascular calcification (VC) using bioinformatics combined with machine learning approaches and to explore the potential underlying mechanisms.…”

Few-Shot Symbol Detection in Engineering Drawings by Laura Jamieson (19759235)

“…<p>Recently, there has been significant interest in digitizing engineering drawings due to their complexity and practical benefits. Symbol digitization, a critical aspect in this field, is challenging as utilizing Deep Learning-based methods to recognize symbols of interest requires a large number of training instances for each class of symbols. …”

Data Sheet 1_Predict and prevent microvascular complications of type 2 diabetes: a cross-sectional and longitudinal study in Chinese communities.docx by Zhaoxiang Liu (9019424)

Analysis of stress-related gene expression in cherry shrimp (<i>N</i>. <i>davidi</i> var. red). by Wei-Wei Hou (3405947)

Correlations between feed additives and color-related genes. by Wei-Wei Hou (3405947)

Table 1_Neural correlates of subjective cognitive decline in Alzheimer’s disease: a systematic review of structural and functional brain changes for early diagnosis and interventio... by Giulia Marafioti (21163931)

“…Dynamic functional connectivity studies report reduced brain activity efficiency, while graph theory analyses show decreased network integration. Advanced neuroimaging techniques and machine learning (ML) approaches demonstrate significant promise in detecting subtle neural changes in SCD, with applications for early diagnosis and monitoring disease progression.…”

Fig 8 - by Abdolhossein Boali (19996390)

Fig 5 - by Abdolhossein Boali (19996390)

The maps illustrating wind erosion in northeastern Iran for 2008 and 2023, generated using various models from the SDM package. by Abdolhossein Boali (19996390)

Importance of variables in the study area in 2023, generated in the R 4.3.2 software (www.r-project.org) and Microsoft Office Excel 2023 (https://www.microsof.com). by Abdolhossein Boali (19996390)

Fig 1 - by Abdolhossein Boali (19996390)

Wind erosion monitoring during the 15 years (2008–2023) using the ensemble model, generated in the ArcGIS 10.7.1 software (www.esri.com) and R 4.3.2 software (www.r-project.org). by Abdolhossein Boali (19996390)