AIMC Topic: Aged, 80 and over

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A Feasible Feature Extraction Method for Atrial Fibrillation Detection From BCG.

IEEE journal of biomedical and health informatics
Atrial fibrillation (AF) is the most frequently occurring form of arrhythmia, which induces multiple fatal diseases and impairs the quality of life in patients; thus, the study of the diagnostic methods for detecting AF is clinically important. Here,...

Prediction of Aneurysm Stability Using a Machine Learning Model Based on PyRadiomics-Derived Morphological Features.

Stroke
Background and Purpose- Discrimination of the stability of intracranial aneurysms is critical for determining the treatment strategy, especially in small aneurysms. This study aims to evaluate the feasibility of applying machine learning for predicti...

Detection of probable dementia cases in undiagnosed patients using structured and unstructured electronic health records.

BMC medical informatics and decision making
BACKGROUND: Dementia is underdiagnosed in both the general population and among Veterans. This underdiagnosis decreases quality of life, reduces opportunities for interventions, and increases health-care costs. New approaches are therefore necessary ...

A radiomics approach based on support vector machine using MR images for preoperative lymph node status evaluation in intrahepatic cholangiocarcinoma.

Theranostics
: Accurate lymph node (LN) status evaluation for intrahepatic cholangiocarcinoma (ICC) patients is essential for surgical planning. This study aimed to develop and validate a prediction model for preoperative LN status evaluation in ICC patients. : A...

Application of artificial neural network model in diagnosis of Alzheimer's disease.

BMC neurology
BACKGROUND: Alzheimer's disease has become a public health crisis globally due to its increasing incidence. The purpose of this study was to establish an early warning model using artificial neural network (ANN) for early diagnosis of AD and to explo...

Identifying incident dementia by applying machine learning to a very large administrative claims dataset.

PloS one
Alzheimer's disease and related dementias (ADRD) are highly prevalent conditions, and prior efforts to develop predictive models have relied on demographic and clinical risk factors using traditional logistical regression methods. We hypothesized tha...

Cortical graph neural network for AD and MCI diagnosis and transfer learning across populations.

NeuroImage. Clinical
Combining machine learning with neuroimaging data has a great potential for early diagnosis of mild cognitive impairment (MCI) and Alzheimer's disease (AD). However, it remains unclear how well the classifiers built on one population can predict MCI/...

In-Bore Transrectal MRI-Guided Biopsy With Robotic Assistance in the Diagnosis of Prostate Cancer: An Analysis of 57 Patients.

AJR. American journal of roentgenology
The objective of our study was to analyze the feasibility and potential role of robotic-assisted transrectal MRI-guided biopsy for the diagnosis of prostate cancer. A total of 57 patients (mean age, 67 ± 6 [SD] years; age range, 57-83 years; mean p...

Development and Validation of a Deep Learning Algorithm for Mortality Prediction in Selecting Patients With Dementia for Earlier Palliative Care Interventions.

JAMA network open
IMPORTANCE: Early palliative care interventions drive high-value care but currently are underused. Health care professionals face challenges in identifying patients who may benefit from palliative care.