AIMC Topic: Aged, 80 and over

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Virtual Monochromatic Imaging of Half-Iodine-Load, Contrast-Enhanced Computed Tomography with Deep Learning Image Reconstruction in Patients with Renal Insufficiency: A Clinical Pilot Study.

Journal of Nippon Medical School = Nippon Ika Daigaku zasshi
BACKGROUND: We retrospectively examined image quality (IQ) of thin-slice virtual monochromatic imaging (VMI) of half-iodine-load, abdominopelvic, contrast-enhanced CT (CECT) by dual-energy CT (DECT) with deep learning image reconstruction (DLIR).

Clinical Application of a Big Data Machine Learning Analysis Model for Osteoporotic Fracture Risk Assessment Built on Multicenter Clinical Data in Qingdao City.

Discovery medicine
BACKGROUND: Osteoporotic fractures (OPF) pose a public health issue, imposing significant burdens on families and societies worldwide. Currently, there is a lack of comprehensive and validated risk assessment models for OPF. This study aims to develo...

Machine learning-enabled risk prediction of self-neglect among community-dwelling older adults in China.

Psychogeriatrics : the official journal of the Japanese Psychogeriatric Society
BACKGROUND: Elder self-neglect (ESN) is usually ignored as a private problem and impairs the health outcomes of older adults. It is essential to construct a robust and efficient tool for risk prediction which can better detect and prevent self-neglec...

Accuracy of Fully Automated and Human-assisted Artificial Intelligence-based CT Quantification of Pleural Effusion Changes after Thoracentesis.

Radiology. Artificial intelligence
Quantifying pleural effusion change at chest CT is important for evaluating disease severity and treatment response. The purpose of this study was to assess the accuracy of artificial intelligence (AI)-based volume quantification of pleural effusion ...

A Multi-Label Deep Learning Model for Detailed Classification of Alzheimer's Disease.

Actas espanolas de psiquiatria
BACKGROUND: Accurate diagnosis and classification of Alzheimer's disease (AD) are crucial for effective treatment and management. Traditional diagnostic models, largely based on binary classification systems, fail to adequately capture the complexiti...

Using voice recognition and machine learning techniques for detecting patient-reported outcomes from conversational voice in palliative care patients.

Japan journal of nursing science : JJNS
AIM: Patient-reported outcome measures (PROMs) are increasingly used in palliative care to evaluate patients' symptoms and conditions. Healthcare providers often collect PROMs through conversations. However, the manual entry of these data into electr...

A Machine Learning Model to Harmonize Volumetric Brain MRI Data for Quantitative Neuroradiologic Assessment of Alzheimer Disease.

Radiology. Artificial intelligence
Purpose To extend a previously developed machine learning algorithm for harmonizing brain volumetric data of individuals undergoing neuroradiologic assessment of Alzheimer disease not encountered during model training. Materials and Methods Neuroharm...

Mini-mental status examination phenotyping for Alzheimer's disease patients using both structured and narrative electronic health record features.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: This study aims to automate the prediction of Mini-Mental State Examination (MMSE) scores, a widely adopted standard for cognitive assessment in patients with Alzheimer's disease, using natural language processing (NLP) and machine learnin...

segcsvd: A Convolutional Neural Network-Based Tool for Quantifying White Matter Hyperintensities in Heterogeneous Patient Cohorts.

Human brain mapping
White matter hyperintensities (WMH) of presumed vascular origin are a magnetic resonance imaging (MRI)-based biomarker of cerebral small vessel disease (CSVD). WMH are associated with cognitive decline and increased risk of stroke and dementia, and a...

Prediction of teicoplanin plasma concentration in critically ill patients: a combination of machine learning and population pharmacokinetics.

The Journal of antimicrobial chemotherapy
BACKGROUND: Teicoplanin has been widely used in patients with infections caused by Staphylococcus aureus, especially for critically ill patients. The pharmacokinetics (PK) of teicoplanin vary between individuals and within the same individual. We aim...