AIMC Topic: Aged
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Smartphone pupillometry with machine learning differentiates ischemic from hemorrhagic stroke: A pilot study.
Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
Dec 12, 2024
OBJECTIVES: Similarities between acute ischemic and hemorrhagic stroke make diagnosis and triage challenging. We studied a smartphone-based quantitative pupillometer for differentiation of acute ischemic and hemorrhagic stroke.
Assessment of the stability of intracranial aneurysms using a deep learning model based on computed tomography angiography.
La Radiologia medica
Dec 12, 2024
PURPOSE: Assessment of the stability of intracranial aneurysms is important in the clinic but remains challenging. The aim of this study was to construct a deep learning model (DLM) to identify unstable aneurysms on computed tomography angiography (C...
Screening for Depression and Anxiety Using a Nonverbal Working Memory Task in a Sample of Older Brazilians: Observational Study of Preliminary Artificial Intelligence Model Transferability.
JMIR formative research
Dec 12, 2024
BACKGROUND: Anxiety and depression represent prevalent yet frequently undetected mental health concerns within the older population. The challenge of identifying these conditions presents an opportunity for artificial intelligence (AI)-driven, remote...
Retinal fluid quantification using a novel deep learning algorithm in patients treated with faricimab in the TRUCKEE study.
Eye (London, England)
Dec 11, 2024
BACKGROUND: Investigate retinal fluid changes via a novel deep-learning algorithm in real-world patients receiving faricimab for the treatment of neovascular age-related macular degeneration (nAMD).
Artificial Intelligence-Driven Assessment of Coronary Computed Tomography Angiography for Intermediate Stenosis: Comparison With Quantitative Coronary Angiography and Fractional Flow Reserve.
The American journal of cardiology
Dec 11, 2024
We aimed to compare artificial intelligence (AI)-based coronary stenosis evaluation of coronary computed tomography angiography (CCTA) with its quantitative counterpart of invasive coronary angiography (ICA) and invasive fractional flow reserve (FFR)...
Residual risk prediction in anticoagulated patients with atrial fibrillation using machine learning: A report from the GLORIA-AF registry phase II/III.
European journal of clinical investigation
Dec 11, 2024
BACKGROUND: Although oral anticoagulation decreases the risk of thromboembolism in patients with atrial fibrillation (AF), a residual risk of thrombotic events still exists. This study aimed to construct machine learning (ML) models to predict the re...
Thromboembolism
Male
Algorithms
Middle Aged
Ischemic Stroke
Myocardial Infarction
Humans
Female
Risk Assessment
Area Under Curve
Thrombosis
Machine Learning
Risk Factors
ROC Curve
Administration, Oral
Anticoagulants
Aged
Atrial Fibrillation
Logistic Models
Registries
Aged, 80 and over
Ischemic Attack, Transient
Stroke
Novel models based on machine learning to predict the prognosis of metaplastic breast cancer.
Breast (Edinburgh, Scotland)
Dec 11, 2024
BACKGROUND: Metaplastic breast cancer (MBC) is a rare and highly aggressive histological subtype of breast cancer. There remains a significant lack of precise predictive models available for use in clinical practice.
Breath-hold diffusion-weighted MR imaging (DWI) using deep learning reconstruction: Comparison with navigator triggered DWI in patients with malignant liver tumors.
Radiography (London, England : 1995)
Dec 11, 2024
INTRODUCTION: This study investigated the feasibility of single breath-hold (BH) diffusion-weighted MR imaging (DWI) using deep learning reconstruction (DLR) compared to navigator triggered (NT) DWI in patients with malignant liver tumors.
Prediction of gene expression-based breast cancer proliferation scores from histopathology whole slide images using deep learning.
BMC cancer
Dec 11, 2024
BACKGROUND: In breast cancer, several gene expression assays have been developed to provide a more personalised treatment. This study focuses on the prediction of two molecular proliferation signatures: an 11-gene proliferation score and the MKI67 pr...
Early Detection of Dementia in Populations With Type 2 Diabetes: Predictive Analytics Using Machine Learning Approach.
Journal of medical Internet research
Dec 11, 2024
BACKGROUND: The possible association between diabetes mellitus and dementia has raised concerns, given the observed coincidental occurrences.
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