AIMC Topic: Adult

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A quantitative evaluation of the deep learning model of segmentation and measurement of cervical spine MRI in healthy adults.

Journal of applied clinical medical physics
PURPOSE: To evaluate the 3D U-Net model for automatic segmentation and measurement of cervical spine structures using magnetic resonance (MR) images of healthy adults.

Toward the eradication of medical diagnostic errors.

Science (New York, N.Y.)
The medical community does not broadcast the problem, but there are many studies that have reinforced a serious issue with diagnostic errors. A recent study concluded: "We estimate that nearly 800,000 Americans die or are permanently disabled by diag...

Added value of dynamic contrast-enhanced MR imaging in deep learning-based prediction of local recurrence in grade 4 adult-type diffuse gliomas patients.

Scientific reports
Local recurrences in patients with grade 4 adult-type diffuse gliomas mostly occur within residual non-enhancing T2 hyperintensity areas after surgical resection. Unfortunately, it is challenging to distinguish non-enhancing tumors from edema in the ...

GlioPredictor: a deep learning model for identification of high-risk adult IDH-mutant glioma towards adjuvant treatment planning.

Scientific reports
Identification of isocitrate dehydrogenase (IDH)-mutant glioma patients at high risk of early progression is critical for radiotherapy treatment planning. Currently tools to stratify risk of early progression are lacking. We sought to identify a comb...

Machine learning in the prediction of massive transfusion in trauma: a retrospective analysis as a proof-of-concept.

European journal of trauma and emergency surgery : official publication of the European Trauma Society
PURPOSE: Early administration and protocolization of massive hemorrhage protocols (MHP) has been associated with decreases in mortality, multiorgan system failure, and number of blood products used. Various prediction tools have been developed for th...

Multiparametric MRI model to predict molecular subtypes of breast cancer using Shapley additive explanations interpretability analysis.

Diagnostic and interventional imaging
PURPOSE: The purpose of this study was to assess the predictive performance of multiparametric magnetic resonance imaging (MRI) for molecular subtypes and interpret features using SHapley Additive exPlanations (SHAP) analysis.

Efficacy of stereotactic body radiotherapy and response prediction using artificial intelligence in oligometastatic gynaecologic cancer.

Gynecologic oncology
PURPOSE: We present a large real-world multicentric dataset of ovarian, uterine and cervical oligometastatic lesions treated with SBRT exploring efficacy and clinical outcomes. In addition, an exploratory machine learning analysis was performed.

[Development of prognostic clinical and genetic models of the risk of low bone mineral density using neural network training].

Problemy endokrinologii
BACKGROUND: Osteoporosis is a common age-related disease with disabling consequences, the early diagnosis of which is difficult due to its long and hidden course, which often leads to diagnosis only after a fracture. In this regard, great expectation...

Human Gait Entrainment to Soft Robotic Hip Perturbation During Simulated Overground Walking.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Entraining human gait with a periodic mechanical perturbation has been proposed as a potentially effective strategy for gait rehabilitation, but the related studies have mostly depended on the use of a fixed-speed treadmill (FST) due to various pract...