AIMC Topic: Aged
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Fast prediction of personalized abdominal organ doses from CT examinations by radiomics feature-based machine learning models.
Scientific reports
Aug 20, 2024
The X-rays emitted during CT scans can increase solid cancer risks by damaging DNA, with the risk tied to patient-specific organ doses. This study aims to establish a new method to predict patient specific abdominal organ doses from CT examinations u...
Linking disease activity with optical coherence tomography angiography in neovascular age related macular degeneration using artificial intelligence.
Scientific reports
Aug 20, 2024
To investigate quantitative associations between AI-assessed disease activity and optical coherence tomography angiography (OCTA)-derived parameters in patients with neovascular age-related macular degeneration (nAMD) undergoing anti-VEGF therapy. OC...
Indirect reference interval estimation using a convolutional neural network with application to cancer antigen 125.
Scientific reports
Aug 20, 2024
Indirect methods for reference interval (RI) estimation, which use data acquired from routine pathology testing, have the potential to accelerate the establishment of RIs to account for variables such as gender and age to improve clinical assessments...
Decoding myasthenia gravis: advanced diagnosis with infrared spectroscopy and machine learning.
Scientific reports
Aug 20, 2024
Myasthenia Gravis (MG) is a rare neurological disease. Although there are intensive efforts, the underlying mechanism of MG still has not been fully elucidated, and early diagnosis is still a question mark. Diagnostic paraclinical tests are also time...
Utilizing machine learning to tailor radiotherapy and chemoradiotherapy for low-grade glioma patients.
PloS one
Aug 20, 2024
BACKGROUND: There is ongoing uncertainty about the effectiveness of various adjuvant treatments for low-grade gliomas (LGGs). Machine learning (ML) models that predict individual treatment effects (ITE) and provide treatment recommendations could hel...
Assessing Consciousness in Patients With Disorders of Consciousness Using a Musical Stimulation Paradigm and Verifiable Criteria.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Aug 20, 2024
Numerous studies have shown that musical stimulation can activate corresponding functional brain areas. Electroencephalogram (EEG) activity during musical stimulation can be used to assess the consciousness states of patients with disorders of consci...
Deep Learning-Based Model for Non-invasive Hemoglobin Estimation via Body Parts Images: A Retrospective Analysis and a Prospective Emergency Department Study.
Journal of imaging informatics in medicine
Aug 19, 2024
Anemia is a significant global health issue, affecting over a billion people worldwide, according to the World Health Organization. Generally, the gold standard for diagnosing anemia relies on laboratory measurements of hemoglobin. To meet the need i...
FRELSA: A dataset for frailty in elderly people originated from ELSA and evaluated through machine learning models.
International journal of medical informatics
Aug 19, 2024
BACKGROUND: Frailty is an age-related syndrome characterized by loss of strength and exhaustion and associated with multi-morbidity. Early detection and prediction of the appearance of frailty could help older people age better and prevent them from ...
Unsupervised machine learning to identify subphenotypes among cardiac intensive care unit patients with heart failure.
ESC heart failure
Aug 19, 2024
AIMS: Hospitalized patients with heart failure (HF) are a heterogeneous population, with multiple phenotypes proposed. Prior studies have not examined the biological phenotypes of critically ill patients with HF admitted to the contemporary cardiac i...
Prediction of intraoperative hypotension using deep learning models based on non-invasive monitoring devices.
Journal of clinical monitoring and computing
Aug 19, 2024
PURPOSE: Intraoperative hypotension is associated with adverse outcomes. Predicting and proactively managing hypotension can reduce its incidence. Previously, hypotension prediction algorithms using artificial intelligence were developed for invasive...
Middle Aged
Deep Learning
Monitoring, Intraoperative
ROC Curve
Photoplethysmography
Humans
Reproducibility of Results
Artificial Intelligence
Aged
Algorithms
Adult
Databases, Factual
Hypotension
Male
Female
Electrocardiography
Intraoperative Complications
Consciousness Monitors
Blood Pressure Determination
Blood Pressure Monitors
Blood Pressure
Capnography
Area Under Curve
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