AIMC Topic: Aged

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Phenotype Discovery and Geographic Disparities of Late-Stage Breast Cancer Diagnosis across U.S. Counties: A Machine Learning Approach.

Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology
BACKGROUND: Disparities in the stage at diagnosis for breast cancer have been independently associated with various contextual characteristics. Understanding which combinations of these characteristics indicate highest risk, and where they are locate...

Artificial intelligence strategy integrating morphologic and architectural biomarkers provides robust diagnostic accuracy for disease progression in chronic lymphocytic leukemia.

The Journal of pathology
Artificial intelligence-based tools designed to assist in the diagnosis of lymphoid neoplasms remain limited. The development of such tools can add value as a diagnostic aid in the evaluation of tissue samples involved by lymphoma. A common diagnosti...

How prevalent and severe is addiction on GABAmimetic drugs in an elderly German general hospital population? Focus on gabapentinoids, benzodiazepines, and z-hypnotic drugs.

Human psychopharmacology
OBJECTIVE: Gabapentinoids (GPT) are reported to be increasingly misused by opioid- and polydrug-users, but the addictive potential of GPT outside of these populations remains understudied. Investigations comparing GPT abuse and dependence liability t...

A qualitative exploration of care homes workers' views and training needs in relation to the use of socially assistive humanoid robots in their workplace.

International journal of older people nursing
AIM: The study aimed to explore the views and attitudes of care home workers about the socially assistive robot that was trialled in their workplace, in order to identify training needs in relation to the hypothetical future use of these robots in th...

A parallel attention-augmented bilinear network for early magnetic resonance imaging-based diagnosis of Alzheimer's disease.

Human brain mapping
Structural magnetic resonance imaging (sMRI) can capture the spatial patterns of brain atrophy in Alzheimer's disease (AD) and incipient dementia. Recently, many sMRI-based deep learning methods have been developed for AD diagnosis. Some of these met...

Predictive value of red blood cell distribution width in septic shock patients with thrombocytopenia: A retrospective study using machine learning.

Journal of clinical laboratory analysis
BACKGROUND: Sepsis-associated thrombocytopenia (SAT) is common in critical patients and results in the elevation of mortality. Red cell distribution width (RDW) can reflect body response to inflammation and oxidative stress. We try to investigate the...

The Influence of Robot-Assisted Learning System on Health Literacy and Learning Perception.

International journal of environmental research and public health
Healthy aging is a new challenge for the world. Therefore, health literacy education is a key issue in the current health care field. This research has developed a robot-assisted learning system to explore the possibility of significantly improving h...

Utility of a Deep Learning Algorithm for Detection of Reticular Opacity on Chest Radiography in Patients With Interstitial Lung Disease.

AJR. American journal of roentgenology
Deep learning has been heavily explored for pulmonary nodule detection on chest radiographs. Detection of reticular opacity in interstitial lung disease (ILD) is challenging and may also benefit from a deep learning algorithm (DLA). The purpose of ...

Predictive modeling for 14-day unplanned hospital readmission risk by using machine learning algorithms.

BMC medical informatics and decision making
BACKGROUND: Early unplanned hospital readmissions are associated with increased harm to patients, increased medical costs, and negative hospital reputation. With the identification of at-risk patients, a crucial step toward improving care, appropriat...

Performance evaluation in [18F]Florbetaben brain PET images classification using 3D Convolutional Neural Network.

PloS one
High accuracy has been reported in deep learning classification for amyloid brain scans, an important factor in Alzheimer's disease diagnosis. However, the possibility of overfitting should be considered, as this model is fitted with sample data. The...