AIMC Topic: Humans

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NLP modeling recommendations for restricted data availability in clinical settings.

BMC medical informatics and decision making
BACKGROUND: Clinical decision-making in healthcare often relies on unstructured text data, which can be challenging to analyze using traditional methods. Natural Language Processing (NLP) has emerged as a promising solution, but its application in cl...

Physics-informed machine learning for automatic model reduction in chemical reaction networks.

Scientific reports
Physics-informed machine learning bridges the gap between the high fidelity of mechanistic models and the adaptive insights of artificial intelligence. In chemical reaction network modeling, this synergy proves valuable, addressing the high computati...

Configural processing as an optimized strategy for robust object recognition in neural networks.

Communications biology
Configural processing, the perception of spatial relationships among an object's components, is crucial for object recognition, yet its teleology and underlying mechanisms remain unclear. We hypothesize that configural processing drives robust recogn...

Early prediction of postpartum dyslipidemia in gestational diabetes using machine learning models.

Scientific reports
This study addresses a gap in research on predictive models for postpartum dyslipidemia in women with gestational diabetes mellitus (GDM). The goal was to develop a machine learning-based model to predict postpartum dyslipidemia using early pregnancy...

Continuous nursing symptom management in cancer chemotherapy patients using deep learning.

Scientific reports
To assess the efficacy of a deep learning platform for managing symptoms in chemotherapy patients, aiming to enhance their quality of life. A non-randomized controlled trial was conducted from September 2022 to March 2024, involving 144 chemotherapy ...

Hybrid neural network method for damage localization in structural health monitoring.

Scientific reports
The detection of cracks in large structures is of critical importance, as such damage can result not only in significant financial costs but also pose serious risks to public safety. Many existing methods for crack detection rely on deep learning alg...

Skin lesion segmentation with a multiscale input fusion U-Net incorporating Res2-SE and pyramid dilated convolution.

Scientific reports
Skin lesion segmentation is crucial for identifying and diagnosing skin diseases. Accurate segmentation aids in identifying and localizing diseases, monitoring morphological changes, and extracting features for further diagnosis, especially in the ea...

Economics of AI and human task sharing for decision making in screening mammography.

Nature communications
The rising global incidence of breast cancer and the persistent shortage of specialized radiologists have heightened the demand for innovative solutions in mammography screening. Artificial intelligence (AI) has emerged as a promising tool to bridge ...

Diagnostic Performance of Artificial Intelligence-Based Methods for Tuberculosis Detection: Systematic Review.

Journal of medical Internet research
BACKGROUND: Tuberculosis (TB) remains a significant health concern, contributing to the highest mortality among infectious diseases worldwide. However, none of the various TB diagnostic tools introduced is deemed sufficient on its own for the diagnos...