AIMC Topic: Aged, 80 and over
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Artificial Intelligence to Predict the Risk of Lymph Node Metastasis in T2 Colorectal Cancer.
Annals of surgery
Jul 30, 2024
OBJECTIVE: To develop and externally validate an updated artificial intelligence (AI) prediction system for stratifying the risk of lymph node metastasis (LNM) in T2 colorectal cancer (CRC).
The impact of high-order features on performance of radiomics studies in CT non-small cell lung cancer.
Clinical imaging
Jul 30, 2024
High-order radiomic features have been shown to produce high performance models in a variety of scenarios. However, models trained without high-order features have shown similar performance, raising the question of whether high-order features are wor...
Deep learning-based automatic ASPECTS calculation can improve diagnosis efficiency in patients with acute ischemic stroke: a multicenter study.
European radiology
Jul 27, 2024
OBJECTIVES: The Alberta Stroke Program Early CT Score (ASPECTS), a systematic method for assessing ischemic changes in acute ischemic stroke using non-contrast computed tomography (NCCT), is often interpreted relying on expert experience and can vary...
Bloodstream infection: Derivation and validation of a reliable and multidimensional prognostic score based on a machine learning model (BLISCO).
American journal of infection control
Jul 26, 2024
BACKGROUND: A bloodstream infection (BSI) prognostic score applicable at the time of blood culture collection is missing.
Identification of profiles associated with conversions between the Alzheimer's disease stages, using a machine learning approach.
Alzheimer's research & therapy
Jul 26, 2024
BACKGROUND: The identification of factors involved in the conversion across the different Alzheimer's disease (AD) stages is crucial to prevent or slow the disease progression. We aimed to assess the factors and their combination associated with the ...
Impact of Downsampling Size and Interpretation Methods on Diagnostic Accuracy in Deep Learning Model for Breast Cancer Using Digital Breast Tomosynthesis Images.
The Tohoku journal of experimental medicine
Jul 25, 2024
While deep learning (DL) models have shown promise in breast cancer diagnosis using digital breast tomosynthesis (DBT) images, the impact of varying matrix sizes and image interpolation methods on diagnostic accuracy remains unclear. Understanding th...
Integrating multi-task and cost-sensitive learning for predicting mortality risk of chronic diseases in the elderly using real-world data.
International journal of medical informatics
Jul 25, 2024
BACKGROUND AND OBJECTIVE: Real-world data encompass population diversity, enabling insights into chronic disease mortality risk among the elderly. Deep learning excels on large datasets, offering promise for real-world data. However, current models f...
Comparison of Explainable Artificial Intelligence Model and Radiologist Review Performances to Detect Breast Cancer in 752 Patients.
Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
Jul 25, 2024
OBJECTIVES: Breast cancer is a type of cancer caused by the uncontrolled growth of cells in the breast tissue. In a few cases, erroneous diagnosis of breast cancer by specialists and unnecessary biopsies can lead to various negative consequences. In ...
Multi-reader multiparametric DECT study evaluating different strengths of iterative and deep learning-based image reconstruction techniques.
European radiology
Jul 24, 2024
OBJECTIVES: To perform a multi-reader comparison of multiparametric dual-energy computed tomography (DECT) images reconstructed with deep-learning image reconstruction (DLIR) and standard-of-care adaptive statistical iterative reconstruction-V (ASIR-...
Development and External Validation of a Machine Learning-based Fall Prediction Model for Nursing Home Residents: A Prospective Cohort Study.
Journal of the American Medical Directors Association
Jul 24, 2024
OBJECTIVES: To develop and externally validate a machine learning-based fall prediction model for ambulatory nursing home residents. The focus is on predicting fall occurrences within 6 months after baseline assessment through a binary classification...
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