AIMC Topic: Aged
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Deep learning image reconstruction for low-kiloelectron volt virtual monoenergetic images in abdominal dual-energy CT: medium strength provides higher lesion conspicuity.
Acta radiologica (Stockholm, Sweden : 1987)
Jul 21, 2024
BACKGROUND: The best settings of deep learning image reconstruction (DLIR) algorithm for abdominal low-kiloelectron volt (keV) virtual monoenergetic imaging (VMI) have not been determined.
Middle Aged
Humans
Radiography, Abdominal
Deep Learning
Image Processing, Computer-Assisted
Algorithms
Aged
Radiography, Dual-Energy Scanned Projection
Radiographic Image Interpretation, Computer-Assisted
Retrospective Studies
Aged, 80 and over
Signal-To-Noise Ratio
Tomography, X-Ray Computed
Adult
Female
Male
Deep representation learning from electronic medical records identifies distinct symptom based subtypes and progression patterns for COVID-19 prognosis.
International journal of medical informatics
Jul 20, 2024
OBJECTIVE: Symptoms are significant kind of phenotypes for managing and controlling of the burst of acute infectious diseases, such as COVID-19. Although patterns of symptom clusters and time series have been considered the high potential prediction ...
Retrospective analysis of interpretable machine learning in predicting ICU thrombocytopenia in geriatric ICU patients.
Scientific reports
Jul 20, 2024
We developed an interpretable machine learning algorithm that prospectively predicts the risk of thrombocytopenia in older critically ill patients during their stay in the intensive care unit (ICU), ultimately aiding clinical decision-making and impr...
Deploying artificial intelligence in the detection of adult appendicular and pelvic fractures in the Singapore emergency department after hours: efficacy, cost savings and non-monetary benefits.
Singapore medical journal
Jul 19, 2024
INTRODUCTION: Radiology plays an integral role in fracture detection in the emergency department (ED). After hours, when there are fewer reporting radiologists, most radiographs are interpreted by ED physicians. A minority of these interpretations ma...
Prognosticating global functional outcome in the recurrent ischemic stroke using baseline clinical and pre-clinical features: A machine learning study.
Journal of evaluation in clinical practice
Jul 19, 2024
BACKGROUND AND PURPOSE: Recurrent ischemic stroke (RIS) induces additional functional limitations in patients. Prognosticating globally functional outcome (GFO) in RIS patients is thereby important to plan a suitable rehabilitation programme. This st...
Radiomics based on multiple machine learning methods for diagnosing early bone metastases not visible on CT images.
Skeletal radiology
Jul 19, 2024
OBJECTIVES: This study utilizes [Tc]-methylene diphosphate (MDP) single photon emission computed tomography (SPECT) images as a reference standard to evaluate whether the integration of radiomics features from computed tomography (CT) and machine lea...
Deep learning-assisted two-dimensional transperineal ultrasound for analyzing bladder neck motion in women with stress urinary incontinence.
American journal of obstetrics and gynecology
Jul 19, 2024
BACKGROUND: No universally recognized transperineal ultrasound parameters are available for evaluating stress urinary incontinence. The information captured by commonly used perineal ultrasound parameters is limited and insufficient for a comprehensi...
Deep learning-based 3D quantitative total tumor burden predicts early recurrence of BCLC A and B HCC after resection.
European radiology
Jul 19, 2024
OBJECTIVES: This study aimed to evaluate the potential of deep learning (DL)-assisted automated three-dimensional quantitative tumor burden at MRI to predict postoperative early recurrence (ER) of hepatocellular carcinoma (HCC).
Artificial Intelligence-Based Histopathological Subtyping of High-Grade Serous Ovarian Cancer.
The American journal of pathology
Jul 19, 2024
Four subtypes of ovarian high-grade serous carcinoma (HGSC) have previously been identified, each with different prognoses and drug sensitivities. However, the accuracy of classification depended on the assessor's experience. This study aimed to deve...
Integrated image-based deep learning and language models for primary diabetes care.
Nature medicine
Jul 19, 2024
Primary diabetes care and diabetic retinopathy (DR) screening persist as major public health challenges due to a shortage of trained primary care physicians (PCPs), particularly in low-resource settings. Here, to bridge the gaps, we developed an inte...
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