The aim of this study is to investigate the relationship of 18 radiomorphometric parameters of panoramic radiographs based on age, and to estimate the age group of people with permanent dentition in a non-invasive, comprehensive, and accurate manner ...
One of the most promising research areas in the healthcare industry and the scientific community is focusing on the AI-based applications for real medical challenges such as the building of computer-aided diagnosis (CAD) systems for breast cancer. Tr...
Topics in magnetic resonance imaging : TMRI
Jun 28, 2022
OBJECTIVES: Automated whole brain segmentation from magnetic resonance images is of great interest for the development of clinically relevant volumetric markers for various neurological diseases. Although deep learning methods have demonstrated remar...
Computational and mathematical methods in medicine
Jun 28, 2022
OBJECTIVE: Vitamin D is associated with neurological deficits in patients with cerebral infarction. This study uses machine learning to evaluate the prediction model's efficacy of the correlation between vitamin D and neurological deficit in patients...
The timely identification of cohort participants at higher risk for attrition is important to earlier interventions and efficient use of research resources. Machine learning may have advantages over the conventional approaches to improve discriminati...
The exponential rise in advanced software computing and low-cost hardware has broadened the horizon for the Internet of Medical Things (IoMT), interoperable e-Healthcare systems serving varied purposes including electronic healthcare records (EHRs) a...
BACKGROUND: Myocardial infarction can lead to malignant arrhythmia, heart failure, and sudden death. Clinical studies have shown that early identification of and timely intervention for acute MI can significantly reduce mortality. The traditional MI ...
Computational intelligence and neuroscience
May 31, 2022
Logistics distribution vehicle scheduling plays an important role in the supply chain. With the wide application of e-commerce technology and the increasing diversification of urban industrial and commercial development mode, the optimal scheduling o...
To observe the clinical efficacy of early enteral nutrition application in critically ill neurosurgical patients, in this paper, we have developed a prediction model for enteral nutrition support in neurosurgical intensive care patients which is prim...
BACKGROUNDS: We aimed to develop and validate machine learning (ML) models for 30-day stroke mortality for mortality risk stratification and as benchmarking models for quality improvement in stroke care.
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