AIMC Topic: Middle Aged

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Real-time coronary artery stenosis detection based on modern neural networks.

Scientific reports
Invasive coronary angiography remains the gold standard for diagnosing coronary artery disease, which may be complicated by both, patient-specific anatomy and image quality. Deep learning techniques aimed at detecting coronary artery stenoses may fac...

Clinical validation of a commercially available deep learning software for synthetic CT generation for brain.

Radiation oncology (London, England)
BACKGROUND: Most studies on synthetic computed tomography (sCT) generation for brain rely on in-house developed methods. They often focus on performance rather than clinical feasibility. Therefore, the aim of this work was to validate sCT images gene...

Predicting cell invasion in breast tumor microenvironment from radiological imaging phenotypes.

BMC cancer
BACKGROUND: The abundance of immune and stromal cells in the tumor microenvironment (TME) is informative of levels of inflammation, angiogenesis, and desmoplasia. Radiomics, an approach of extracting quantitative features from radiological imaging to...

A Multimodality Machine Learning Approach to Differentiate Severe and Nonsevere COVID-19: Model Development and Validation.

Journal of medical Internet research
BACKGROUND: Effectively and efficiently diagnosing patients who have COVID-19 with the accurate clinical type of the disease is essential to achieve optimal outcomes for the patients as well as to reduce the risk of overloading the health care system...

Mycophenolic Acid Exposure Prediction Using Machine Learning.

Clinical pharmacology and therapeutics
Therapeutic drug monitoring of mycophenolic acid (MPA) based on area under the curve (AUC) is well-established and machine learning (ML) approaches could help to estimate AUC. The aim of this work is to estimate the AUC of MPA in organ transplant pat...

Identifying multiple sclerosis subtypes using unsupervised machine learning and MRI data.

Nature communications
Multiple sclerosis (MS) can be divided into four phenotypes based on clinical evolution. The pathophysiological boundaries of these phenotypes are unclear, limiting treatment stratification. Machine learning can identify groups with similar features ...

Applying Machine Learning Across Sites: External Validation of a Surgical Site Infection Detection Algorithm.

Journal of the American College of Surgeons
BACKGROUND: Surgical complications have tremendous consequences and costs. Complication detection is important for quality improvement, but traditional manual chart review is burdensome. Automated mechanisms are needed to make this more efficient. To...

Application of artificial intelligence using a convolutional neural network for detecting cholesteatoma in endoscopic enhanced images.

Auris, nasus, larynx
OBJECTIVE: We examined whether artificial intelligence (AI) used with the novel digital image enhancement system modalities (CLARA+CHROMA, SPECTRA A, and SPECTRA B) could distinguish the cholesteatoma matrix, cholesteatoma debris, and normal middle e...