Online bearing fault diagnosis using numerical simulation models and machine learning classifications

H Wang, J Zheng, J Xiang - Reliability Engineering & System Safety, 2023 - Elsevier
Digital twin (DT) is the embodiment of the most advanced achievements of the current
simulation technology theory development and the direction of intelligent development in the …

The robustness of counterfactual explanations over time

A Ferrario, M Loi - Ieee Access, 2022 - ieeexplore.ieee.org
Counterfactual explanations are a prominent example of post-hoc interpretability methods in
the explainable Artificial Intelligence (AI) research domain. Differently from other explanation …

Machine learning models to detect social distress, spiritual pain, and severe physical psychological symptoms in terminally ill patients with cancer from unstructured …

K Masukawa, M Aoyama, S Yokota… - Palliative …, 2022 - journals.sagepub.com
Background: Few studies have developed automatic systems for identifying social distress,
spiritual pain, and severe physical and phycological symptoms from text data in electronic …

Charting everyday activities in later life: Study protocol of the mobility, activity, and social interactions study (MOASIS)

C Röcke, M Luo, P Bereuter, M Katana… - Frontiers in …, 2023 - frontiersin.org
Prominent theories of aging emphasize the importance of resource allocation processes as
a means to maintain functional ability, well-being and quality of life. Little is known about …

[HTML][HTML] Predicting the next-day perceived and physiological stress of pregnant women by using machine learning and explainability: algorithm development and …

A Ng, B Wei, J Jain, EA Ward, SD Tandon… - JMIR mHealth and …, 2022 - mhealth.jmir.org
Background Cognitive behavioral therapy–based interventions are effective in reducing
prenatal stress, which can have severe adverse health effects on mothers and newborns if …

Year 2020 (with covid): Observation of scientific literature on clinical natural language processing

N Grabar, C Grouin - Yearbook of Medical Informatics, 2021 - thieme-connect.com
Objectives: To analyze the content of publications within the medical NLP domain in 2020.
Methods: Automatic and manual preselection of publications to be reviewed, and selection …

[HTML][HTML] Non-invasively discriminating the pathological subtypes of non-small cell lung cancer with pretreatment 18F-FDG PET/CT using deep learning

H Zhao, Y Su, Z Lyu, L Tian, P Xu, L Lin, W Han… - Academic Radiology, 2024 - Elsevier
Rationale and Objectives To develop an end-to-end deep learning (DL) model for non-
invasively predicting non-small cell lung cancer (NSCLC) pathological subtypes based on …

[HTML][HTML] Predicting working memory in healthy older adults using real-life language and social context information: a machine learning approach

A Ferrario, M Luo, AJ Polsinelli, SA Moseley, MR Mehl… - JMIR aging, 2022 - aging.jmir.org
Background Language use and social interactions have demonstrated a close relationship
with cognitive measures. It is important to improve the understanding of language use and …

Understanding reminiscence and its negative functions in the everyday conversations of young adults: A machine learning approach

A Ferrario, B Demiray - Heliyon, 2024 - cell.com
Reminiscence is the act of recalling or telling others about relevant personal past
experiences. It is an important activity for all individuals, young and old alike. In fact …

With a little help from familiar interlocutors: Real-world language use in young and older adults

M Luo, R Debelak, G Schneider, M Martin… - Aging & Mental …, 2021 - Taylor & Francis
Objectives Functional psychologists are concerned with the performance of cognitive
activities in the real world in relation to cognitive changes in older age. Conversational …