AIMC Topic: Aged
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Elevating Patient Care With Deep Learning: High-Resolution Cervical Auscultation Signals for Swallowing Kinematic Analysis in Nasogastric Tube Patients.
IEEE journal of translational engineering in health and medicine
Nov 13, 2024
Patients with nasogastric (NG) tubes require careful monitoring due to the potential impact of the tube on their ability to swallow safely. This study aimed to investigate the utility of high-resolution cervical auscultation (HRCA) signals in assessi...
Next-visit prediction and prevention of hypertension using large-scale routine health checkup data.
PloS one
Nov 13, 2024
This paper proposes the use of machine learning models to predict one's risk of having hypertension in the future using their routine health checkup data of their current and past visits to a health checkup center. The large-scale and high-dimensiona...
Machine learning algorithms using the inflammatory prognostic index for contrast-induced nephropathy in NSTEMI patients.
Biomarkers in medicine
Nov 13, 2024
Inflammatory prognostic index (IPI), has been shown to be related with poor outcomes in cancer patients. We aimed to investigate the predictive role of IPI for contrast-induced nephropathy (CIN) development in non-ST segment elevation myocardial inf...
Predicting post-hepatectomy liver failure in patients with hepatocellular carcinoma: nomograms based on deep learning analysis of gadoxetic acid-enhanced MRI.
European radiology
Nov 12, 2024
OBJECTIVES: This study aimed to develop nomograms for predicting post-hepatectomy liver failure (PHLF) in patients with hepatocellular carcinoma (HCC), using deep learning analysis of Gadoxetic acid-enhanced hepatobiliary (HBP) MRI.
Accuracy of 7 Artificial Intelligence-Based Intraocular Lens Power Calculation Formulas in Extremely Long Caucasian Eyes.
American journal of ophthalmology
Nov 12, 2024
PURPOSE: To compare 7 artificial intelligence (AI)-based intraocular lens (IOL) power calculation formulas in extremely long eyes.
Humans
Artificial Intelligence
Retrospective Studies
Male
Middle Aged
Refraction, Ocular
Lenses, Intraocular
Visual Acuity
Female
Reproducibility of Results
Aged
Aged, 80 and over
Axial Length, Eye
White People
Lens Implantation, Intraocular
Phacoemulsification
Myopia, Degenerative
Biometry
Optics and Photonics
Data-driven explainable machine learning for personalized risk classification of myasthenic crisis.
International journal of medical informatics
Nov 12, 2024
OBJECTIVE: Myasthenic crisis (MC) is a critical progression of Myasthenia gravis (MG), requiring intensive care treatment and invasive therapies. Classifying patients at high-risk for MC facilitates treatment decisions such as changes in medication o...
Development of a Deep Learning Model for Classification of Hepatic Steatosis from Clinical Standard Ultrasound.
Ultrasound in medicine & biology
Nov 12, 2024
OBJECTIVE: Early detection and monitoring of hepatic steatosis can help establish appropriate preventative measures against progression to more advanced disease. We aimed to develop a deep learning (DL) program for classification of hepatic steatosis...
A Novel Machine Learning-based Predictive Model of Clinically Significant Prostate Cancer and Online Risk Calculator.
Urology
Nov 12, 2024
OBJECTIVE: To create a machine-learning predictive model combining prostate imaging-reporting and data system (PI-RADS) score, PSA density, and clinical variables to predict clinically significant prostate cancer (csPCa).
Diagnostic performance of an artificial intelligence model for the detection of pneumothorax at chest X-ray.
Clinical imaging
Nov 12, 2024
PURPOSE: Pneumothorax (PTX) is a common clinical urgency, its diagnosis is usually performed on chest radiography (CXR), and it presents a setting where artificial intelligence (AI) methods could find terrain in aiding radiologists in facing increasi...
Generalizable self-supervised learning for brain CTA in acute stroke.
Computers in biology and medicine
Nov 12, 2024
Acute stroke management involves rapid and accurate interpretation of CTA imaging data. However, generalizable models for multiple acute stroke tasks able to learn from unlabeled data do not exist. We propose a linear probed self-supervised contrasti...
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