AIMC Topic: Aged

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Topographic and quantitative correlation of structure and function using deep learning in subclinical biomarkers of intermediate age-related macular degeneration.

Scientific reports
To examine the morphological impact of deep learning (DL)-quantified biomarkers on point-wise sensitivity (PWS) using microperimetry (MP) and optical coherence tomography (OCT) in intermediate AMD (iAMD). Patients with iAMD were examined by OCT (Spec...

Contrast-enhanced thin-slice abdominal CT with super-resolution deep learning reconstruction technique: evaluation of image quality and visibility of anatomical structures.

Japanese journal of radiology
PURPOSE: To compare image quality and visibility of anatomical structures on contrast-enhanced thin-slice abdominal CT images reconstructed using super-resolution deep learning reconstruction (SR-DLR), deep learning-based reconstruction (DLR), and hy...

Development and validation of a machine learning model to predict the risk of readmission within one year in HFpEF patients: Short title: Prediction of HFpEF readmission.

International journal of medical informatics
BACKGROUND: Heart failure with preserved ejection fraction (HFpEF) is associated with elevated rates of readmission and mortality. Accurate prediction of readmission risk is essential for optimizing healthcare resources and enhancing patient outcomes...

Exploring ChatGPT's potential in ECG interpretation and outcome prediction in emergency department.

The American journal of emergency medicine
BACKGROUND: Approximately 20 % of emergency department (ED) visits involve cardiovascular symptoms. While ECGs are crucial for diagnosing serious conditions, interpretation accuracy varies among emergency physicians. Artificial intelligence (AI), suc...

Automatic AI tool for opportunistic screening of vertebral compression fractures on chest frontal radiographs: A multicenter study.

Bone
Vertebral compression fractures (VCFs) are the most common type of osteoporotic fractures, yet they are often clinically silent and undiagnosed. Chest frontal radiographs (CFRs) are frequently used in clinical practice and a portion of VCFs can be de...

Artificial intelligence modeling of biomarker-based physiological age: Impact on phase 1 drug-metabolizing enzyme phenotypes.

CPT: pharmacometrics & systems pharmacology
Age and aging are important predictors of health status, disease progression, drug kinetics, and effects. The purpose was to develop ensemble learning-based physiological age (PA) models for evaluating drug metabolism. National Health and Nutrition E...

Predicting Fear of Breast Cancer Recurrence in women five years after diagnosis using Machine Learning and healthcare reimbursement data from the French nationwide VICAN survey.

International journal of medical informatics
OBJECTIVE: A major concern for cancer survivors after treatment is the Fear of Cancer Recurrence (FCR), which is the fear that cancer will reappear or progress. This fear can be exacerbated by medical uncertainty about the future, leading to harmful ...

Improved prognostication of overall survival after radiotherapy in lung cancer patients by an interpretable machine learning model integrating lung and tumor radiomics and clinical parameters.

La Radiologia medica
BACKGROUND: Accurate prognostication of overall survival (OS) for non-small cell lung cancer (NSCLC) patients receiving definitive radiotherapy (RT) is crucial for developing personalized treatment strategies. This study aims to construct an interpre...

Automatic localization and deep convolutional generative adversarial network-based classification of focal liver lesions in computed tomography images: A preliminary study.

Journal of gastroenterology and hepatology
BACKGROUND AND AIM: Computed tomography of the abdomen exhibits subtle and complex features of liver lesions, subjectively interpreted by physicians. We developed a deep learning-based localization and classification (DLLC) system for focal liver les...