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Multimodal fusion for anticipating human decision performance.
Scientific reports
Jun 8, 2024
Anticipating human decisions while performing complex tasks remains a formidable challenge. This study proposes a multimodal machine-learning approach that leverages image features and electroencephalography (EEG) data to predict human response corre...
Preservative contact allergy in occupational dermatitis: a machine learning analysis.
Archives of dermatological research
Jun 8, 2024
Occupational dermatoses impose a significant socioeconomic burden. Allergic contact dermatitis related to occupation is prevalent among healthcare workers, cleaning service personnel, individuals in the beauty industry and industrial workers. Among r...
Dynamic and Transdiagnostic Risk Calculator Based on Natural Language Processing for the Prediction of Psychosis in Secondary Mental Health Care: Development and Internal-External Validation Cohort Study.
Biological psychiatry
Jun 7, 2024
BACKGROUND: Automatic transdiagnostic risk calculators can improve the detection of individuals at risk of psychosis. However, they rely on assessment at a single point in time and can be refined with dynamic modeling techniques that account for chan...
AI in medical education: the moderating role of the chilling effect and STARA awareness.
BMC medical education
Jun 7, 2024
BACKGROUND: The rapid growth of artificial intelligence (AI) technologies has been driven by the latest advances in computing power. Although, there exists a dearth of research on the application of AI in medical education.
Development of a machine learning-based model for predicting positive margins in high-grade squamous intraepithelial lesion (HSIL) treatment by Cold Knife Conization(CKC): a single-center retrospective study.
BMC women's health
Jun 7, 2024
OBJECTIVES: This study aims to analyze factors associated with positive surgical margins following cold knife conization (CKC) in patients with cervical high-grade squamous intraepithelial lesion (HSIL) and to develop a machine-learning-based risk pr...
Cryosurgery
Aged
Squamous Intraepithelial Lesions
Conization
Young Adult
Squamous Intraepithelial Lesions of the Cervix
Adult
Uterine Cervical Neoplasms
Machine Learning
Logistic Models
Middle Aged
Humans
Retrospective Studies
Margins of Excision
Female
Papillomavirus Infections
Uterine Cervical Dysplasia
Risk Factors
A Dynamic Window Method Based on Reinforcement Learning for SSVEP Recognition.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Jun 7, 2024
Steady-state visual evoked potential (SSVEP) is one of the most used brain-computer interface (BCI) paradigms. Conventional methods analyze SSVEPs at a fixed window length. Compared with these methods, dynamic window methods can achieve a higher info...
Predicting Musculoskeletal Loading at Common Running Injury Locations Using Machine Learning and Instrumented Insoles.
Medicine and science in sports and exercise
Jun 6, 2024
INTRODUCTION: Wearables have the potential to provide accurate estimates of tissue loads at common running injury locations. Here we investigate the accuracy by which commercially available instrumented insoles (ARION; ATO-GEAR, Eindhoven, The Nether...
Development and external validation of a logistic and a penalized logistic model using machine-learning techniques to predict suicide attempts: A multicenter prospective cohort study in Korea.
Journal of psychiatric research
Jun 6, 2024
Despite previous efforts to build statistical models for predicting the risk of suicidal behavior using machine-learning analysis, a high-accuracy model can lead to overfitting. Furthermore, internal validation cannot completely address this problem....
Exploring the potential of representation and transfer learning for anatomical neuroimaging: Application to psychiatry.
NeuroImage
Jun 6, 2024
The perspective of personalized medicine for brain disorders requires efficient learning models for anatomical neuroimaging-based prediction of clinical conditions. There is now a consensus on the benefit of deep learning (DL) in addressing many medi...
Machine learning thermal comfort prediction models based on occupant demographic characteristics.
Journal of thermal biology
Jun 6, 2024
This study aims to investigate the predictive occupant demographic characteristics of thermal sensation (TS) and thermal satisfaction (TSa) as well as to find the most effective machine learning (ML) algorithms for predicting TS and TSa. To achieve t...
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