AIMC Topic: Aged

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Deep learning and radiomics integration of photoacoustic/ultrasound imaging for non-invasive prediction of luminal and non-luminal breast cancer subtypes.

Breast cancer research : BCR
PURPOSE: This study aimed to develop a Deep Learning Radiomics integrated model (DLRN), which combines photoacoustic/ultrasound(PA/US)imaging with clinical and radiomics features to distinguish between luminal and non-luminal BC in a preoperative set...

Association between geriatric nutritional risk index (GNRI) and asthma in elderly individuals aged 60 and above: a cross-sectional study of the NHANES 2005-2018.

BMC pulmonary medicine
OBJECTIVE: The geriatric nutritional risk index (GNRI) is a promising tool for predicting nutrition-related complications in older adults. This study aimed to explore the association between GNRI and asthma in individuals aged 60 and above.

Temporal trends and machine learning prediction of depressive symptoms among Chinese middle-aged and elderly individuals: a national cohort study.

BMC public health
BACKGROUND: The prevalence of depression symptoms, the third most disabling disease worldwide, is as high as 11.5%-21.1% in China's middle-aged and elderly population and increases significantly with age. It is crucial to identify high-risk groups ef...

Development of a machine learning-based depression risk identification tool for older adults with asthma.

BMC psychiatry
BACKGROUND: Asthma is a chronic inflammatory disorder that adversely affects the quality of life, particularly in older adults. The coexistence of depression in asthma patients complicates their management and exacerbates health outcomes. This study ...

A machine learning approach to identify patients at risk for long-term consequences after pulmonary embolism.

Scientific reports
Pulmonary embolism (PE) can result in long-term sequelae, such as post-PE syndrome, including persistent dyspnea and chronic thromboembolic pulmonary hypertension (CTEPH). Existing prediction tools for severe post-PE complications lack sensitivity an...

The long-term neuroprotective effect of MIND and Mediterranean diet on patients with Alzheimer's disease.

Scientific reports
Alzheimer's disease is a progressive neurodegenerative disorder with no cure, making preventive strategies crucial. Dietary interventions, particularly the Mediterranean (MeDi) and MIND diets, have been associated with reduced cognitive decline, but ...

Machine learning and data-driven inverse modeling of metabolomics unveil key processes of active aging.

NPJ systems biology and applications
Physical inactivity and low fitness have become global health concerns. Metabolomics, as an integrative approach, may link fitness to molecular changes. In this study, we analyzed blood metabolomes from elderly individuals under different treatments....

Development of deep learning-based narrow-band imaging endocytoscopic classification for predicting colorectal lesions from a retrospective study.

Nature communications
Data-driven approaches have advanced colorectal lesion diagnosis in digestive endoscopy, yet their application in endocytoscopy (EC)-a high-magnification imaging technique-remains limited, with most studies relying on conventional machine learning me...

Interpretable Machine Learning Model for Pulmonary Hypertension Risk Prediction: Retrospective Cohort Study.

JMIR medical informatics
BACKGROUND: Pulmonary hypertension (PH) is a progressive disorder characterized by elevated pulmonary artery pressure and increased pulmonary vascular resistance, ultimately leading to right heart failure. Early detection is critical for improving pa...

Exploratory Research With a Health Consumer Group on Social Robot Use Among Older Adults: Qualitative Study.

JMIR human factors
BACKGROUND: There is an increased focus on involving members of the public in health research. These types of groups, such as "health consumer groups," bring different expertise to inform the design of a research study. There is a growing general con...