AIMC Topic: Aged
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A Deep Learning System to Predict Epithelial Dysplasia in Oral Leukoplakia.
Journal of dental research
Oct 9, 2024
Oral leukoplakia (OL) has an inherent disposition to develop oral cancer. OL with epithelial dysplasia (OED) is significantly likely to undergo malignant transformation; however, routine OED assessment is invasive and challenging. This study investig...
Development of HepatIA: A computed tomography annotation platform and database for artificial intelligence training in hepatocellular carcinoma detection at a Brazilian tertiary teaching hospital.
Clinics (Sao Paulo, Brazil)
Oct 9, 2024
BACKGROUND: Hepatocellular carcinoma (HCC) is a prevalent tumor with high mortality rates. Computed tomography (CT) is crucial in the non-invasive diagnosis of HCC. Recent advancements in artificial intelligence (AI) have shown significant potential ...
Machine learning-based identification and validation of aging-related genes in cardiomyocytes from patients with atrial fibrillation.
Minerva cardiology and angiology
Oct 8, 2024
BACKGROUND: Aging is a key risk factor for atrial fibrillation (AF), a prevalent cardiac disorder among the elderly. This study aims to elucidate the genetic underpinnings of AF in the context of aging.
Evaluating the positive predictive value of code-based identification of cirrhosis and its complications utilizing GPT-4.
Hepatology (Baltimore, Md.)
Oct 8, 2024
BACKGROUND AND AIMS: Diagnosis code classification is a common method for cohort identification in cirrhosis research, but it is often inaccurate and augmented by labor-intensive chart review. Natural language processing using large language models (...
Development and validation of the PHM-CPA model to predict in-hospital mortality for cirrhotic patients with acute kidney injury.
Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver
Oct 8, 2024
BACKGROUND: The presence of acute kidney injury (AKI) significantly increases in-hospital mortality risk for cirrhotic patients. Early prognosis prediction for these patients is crucial. We aimed to develop and validate a machine learning model for i...
Clinicopathological features for the prediction of immunosuppressive treatment responses in sarcoidosis-related kidney involvement: a single-center retrospective study.
Turkish journal of medical sciences
Oct 8, 2024
BACKGROUND/AIM: Sarcoidosis is a multisystem disorder that affects many organs, including the kidneys. This single-center retrospective study investigated the clinical, pathological, and laboratory findings of patients with kidney sarcoidosis who wer...
Energy-integrating detector based ultra-high-resolution CT with deep learning reconstruction for the assessment of calcified lesions in coronary artery disease.
Journal of cardiovascular computed tomography
Oct 8, 2024
BACKGROUND: The aim of this study to compare of the image quality of calcified lesions in coronary artery disease between deep learning reconstruction (DLR) and model-based iterative reconstruction (MBIR) on energy-integrating detector (EID) based ul...
Multidetector Computed Tomography
Vascular Calcification
Phantoms, Imaging
Computed Tomography Angiography
Male
Middle Aged
Severity of Illness Index
Deep Learning
Radiographic Image Interpretation, Computer-Assisted
Coronary Artery Disease
Coronary Vessels
Predictive Value of Tests
Coronary Angiography
Retrospective Studies
Female
Reproducibility of Results
Aged
Humans
Machine-Learning-Based Prediction of Photobiomodulation Effects on Older Adults With Cognitive Decline Using Functional Near-Infrared Spectroscopy.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Oct 8, 2024
Transcranial photobiomodulation (tPBM) has been widely studied for its potential to enhance cognitive functions of the elderly. However, its efficacy varies, with some individuals exhibiting no significant response to the treatment. Considering these...
Radial polarisation patterns identify macular damage: a machine learning approach.
Clinical & experimental optometry
Oct 7, 2024
CLINICAL RELEVANCE: Identifying polarisation-modulated patterns may be an effective method for both detecting and monitoring macular damage.
Perceived Impact of COVID-19 in an Underserved Community: A Natural Language Processing Approach.
Journal of advanced nursing
Oct 7, 2024
AIM: To utilise natural language processing (NLP) to analyse interviews about the impact of COVID-19 in underserved communities and to compare it to traditional thematic analysis in a small subset of interviews.
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