AIMC Topic: Aged

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Prognostic accuracy of MALDI-TOF mass spectrometric analysis of plasma in COVID-19.

Life science alliance
SARS-CoV-2 infection poses a global health crisis. In parallel with the ongoing world effort to identify therapeutic solutions, there is a critical need for improvement in the prognosis of COVID-19. Here, we report plasma proteome fingerprinting that...

Improving Prehospital Stroke Diagnosis Using Natural Language Processing of Paramedic Reports.

Stroke
BACKGROUND AND PURPOSE: Accurate prehospital diagnosis of stroke by emergency medical services (EMS) can increase treatments rates, mitigate disability, and reduce stroke deaths. We aimed to develop a model that utilizes natural language processing o...

Predicting lethal courses in critically ill COVID-19 patients using a machine learning model trained on patients with non-COVID-19 viral pneumonia.

Scientific reports
In a pandemic with a novel disease, disease-specific prognosis models are available only with a delay. To bridge the critical early phase, models built for similar diseases might be applied. To test the accuracy of such a knowledge transfer, we inves...

Machine learning-based glucose prediction with use of continuous glucose and physical activity monitoring data: The Maastricht Study.

PloS one
BACKGROUND: Closed-loop insulin delivery systems, which integrate continuous glucose monitoring (CGM) and algorithms that continuously guide insulin dosing, have been shown to improve glycaemic control. The ability to predict future glucose values ca...

Multimodal deep learning with feature level fusion for identification of choroidal neovascularization activity in age-related macular degeneration.

Acta ophthalmologica
PURPOSE: This study aimed to determine the efficacy of a multimodal deep learning (DL) model using optical coherence tomography (OCT) and optical coherence tomography angiography (OCTA) images for the assessment of choroidal neovascularization (CNV) ...

Tissue outcome prediction in hyperacute ischemic stroke: Comparison of machine learning models.

Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism
Machine Learning (ML) has been proposed for tissue fate prediction after acute ischemic stroke (AIS), with the aim to help treatment decision and patient management. We compared three different ML models to the clinical method based on diffusion-perf...

Deep learning for semi-automated unidirectional measurement of lung tumor size in CT.

Cancer imaging : the official publication of the International Cancer Imaging Society
BACKGROUND: Performing Response Evaluation Criteria in Solid Tumor (RECISTS) measurement is a non-trivial task requiring much expertise and time. A deep learning-based algorithm has the potential to assist with rapid and consistent lesion measurement...

Contrasting factors associated with COVID-19-related ICU admission and death outcomes in hospitalised patients by means of Shapley values.

PLoS computational biology
Identification of those at greatest risk of death due to the substantial threat of COVID-19 can benefit from novel approaches to epidemiology that leverage large datasets and complex machine-learning models, provide data-driven intelligence, and guid...

Initial experience with a suprapubic single-port robotic right hemicolectomy in patients with colon cancer.

Techniques in coloproctology
BACKGROUND: We developed a novel suprapubic single-port robotic right hemicolectomy (spRHC) procedure for patients with right colon cancer using a da Vinci SP Surgical System. The aim of this study was to determine the safety and feasibility of this ...

Characterizing the Clinical Features and Atrophy Patterns of -Related Frontotemporal Dementia With Disease Progression Modeling.

Neurology
BACKGROUND AND OBJECTIVE: Mutations in the gene cause frontotemporal dementia (FTD). Most previous studies investigating the neuroanatomical signature of mutations have grouped all different mutations together and shown an association with focal at...