AIMC Topic: Humans

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An architecture for COVID-19 analysis and detection using big data, AI, and data architectures.

PloS one
The COVID-19 epidemic is affecting individuals in many ways and continues to spread all over the world. Vaccines and traditional medical techniques are still being researched. In diagnosis and therapy, biological and digital technology is used to ove...

Uncertainty quantification in neural-network based pain intensity estimation.

PloS one
Improper pain management leads to severe physical or mental consequences, including suffering, a negative impact on quality of life, and an increased risk of opioid dependency. Assessing the presence and severity of pain is imperative to prevent such...

Performance assessment of hybrid machine learning approaches for breast cancer and recurrence prediction.

PloS one
Breast cancer is a major health concern for women everywhere and a major killer of women. Malignant tumors may be distinguished from benign ones, allowing for early diagnosis of this disease. Therefore, doctors need an accurate method of diagnosing t...

Improving human activity classification based on micro-doppler signatures of FMCW radar with the effect of noise.

PloS one
Nowadays, classifying human activities is applied in many essential fields, such as healthcare, security monitoring, and search and rescue missions. Radar sensor-based human activity classification is regarded as a superior approach in comparison to ...

Brain MRI detection and classification: Harnessing convolutional neural networks and multi-level thresholding.

PloS one
Brain tumor detection in clinical applications is a complex and challenging task due to the intricate structures of the human brain. Magnetic Resonance (MR) imaging is widely preferred for this purpose because of its ability to provide detailed image...

Optimizing postprandial glucose prediction through integration of diet and exercise: Leveraging transfer learning with imbalanced patient data.

PloS one
BACKGROUND: In recent years, numerous methods have been introduced to predict glucose levels using machine-learning techniques on patients' daily behavioral and continuous glucose data. Nevertheless, a definitive consensus remains elusive regarding m...

Identification of Key Efferocytosis-Related Genes and Mechanisms in Diabetic Retinopathy.

Molecular biotechnology
This study aimed to explore the key efferocytosis-related genes in diabetic retinopathy (DR) and their regulatory mechanisms. Public DR-related gene expression datasets, GSE160306 (training) and GSE60436 (validation), were downloaded. Differentially ...

A Cloud-Based System for Automated AI Image Analysis and Reporting.

Journal of imaging informatics in medicine
Although numerous AI algorithms have been published, the relatively small number of algorithms used clinically is partly due to the difficulty of implementing AI seamlessly into the clinical workflow for radiologists and for their healthcare enterpri...

Can digital leadership transform AI anxiety and attitude in nurses?

Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing
BACKGROUND: The lack of artificial intelligence applications in nursing education and the nursing profession in Turkey and the need for strategies for integrating artificial intelligence into the nursing profession continues. At this point, there is ...

Automated segmentation and deep learning classification of ductopenic parotid salivary glands in sialo cone-beam CT images.

International journal of computer assisted radiology and surgery
PURPOSE: This study addressed the challenge of detecting and classifying the severity of ductopenia in parotid glands, a structural abnormality characterized by a reduced number of salivary ducts, previously shown to be associated with salivary gland...