AIMC Topic: Female

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Predicting 30-Days Hospital Readmission for Patients with Heart Failure Using Electronic Health Record Embeddings: Comparative Evaluation.

JMIR medical informatics
BACKGROUND: Heart failure (HF) is a public health concern with a wider impact on quality of life and cost of care. One of the major challenges in HF is the higher rate of unplanned readmissions and suboptimal performance of models to predict the read...

A nomogram for predicting renal function recovery after robotic-assisted ureteral reconstruction: development and comparative validation using traditional and machine learning models.

Journal of robotic surgery
OBJECTIVE: To develop, validate, and compare a Traditional Multivariable Logistic Regression model with a Machine Learning-based LASSO Regression Model for predicting significant renal function recovery in adult patients undergoing surgical repair fo...

Breast cancer diagnosis from histopathological images and molecular signatures by fusing features with an explainable AI-based residual tabular network model.

Journal of computer-aided molecular design
Early Breast Cancer (BC) Diagnosis has the potential to cut BC death rates in the long term drastically. Identifying early-stage cancer cells is the most crucial step in determining the best prognosis. Despite recent advances in the use of AI-based m...

Single-channel EEG-based sleep stage classification via hybrid data distillation.

Journal of neural engineering
With the advancement of deep learning technologies, more and more researchers have begun developing end-to-end automatic sleep stage classification frameworks. However, these frameworks typically require access to large electroencephalogram (EEG) dat...

RADIFUSION: a multi-radiomics deep learning based breast cancer risk prediction model using sequential mammographic images with image attention and bilateral asymmetry refinement.

Physics in medicine and biology
Breast cancer is a significant public health concern, and early detection is critical for triaging high-risk patients. Sequential screening mammograms can provide important spatiotemporal information about changes in breast tissue over time, which ma...

Predicting IVF outcomes using a logistic regression-ABC hybrid model: A proof-of-concept study on supplement associations.

PloS one
Machine learning models are increasingly applied to assisted reproductive technologies (ART), yet most studies rely on conventional algorithms with limited optimization. This proof-of-concept study investigates whether a hybrid Logistic Regression-Ar...

The impact of negative emotions on adolescents' nonsuicidal self-injury thoughts: an integrated application of machine learning and multilevel logistic models.

PloS one
Non-Suicidal Self-Injury (NSSI) is a prevalent and complex behavior among adolescents, often linked to negative emotions such as loneliness, anxiety, and emptiness. Traditional self-report and experimental methods rely on autobiographical recall and ...

Association Between Choroid Plexus Morphological Alterations, Alzheimer Pathologies, and Cognitive Impairment: A Longitudinal Study.

Neurology
BACKGROUND AND OBJECTIVES: The choroid plexus (ChP) plays a crucial role in maintaining brain health. Alzheimer disease (AD) pathologies may damage the ChP and accelerate neurodegeneration. Previous imaging studies have found overall increased ChP vo...

Novel insights into predicting the presence of micropapillary and solid components in stage IA lung adenocarcinoma using machine learning models of modifiable risk factors.

Annals of medicine
BACKGROUND: Lung adenocarcinoma (LUAC) patients with micropapillary (MP) and/or solid (S) generally demonstrate a poorer survival prognosis. In the diagnosis and treatment of stage IA LUAC, precisely establishing personalized treatment strategies for...