AIMC Topic: Humans

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WDA: An Improved Wasserstein Distance-Based Transfer Learning Fault Diagnosis Method.

Sensors (Basel, Switzerland)
With the growth of computing power, deep learning methods have recently been widely used in machine fault diagnosis. In order to realize highly efficient diagnosis accuracy, people need to know the detailed health condition of collected signals from ...

Egocentric-View Fingertip Detection for Air Writing Based on Convolutional Neural Networks.

Sensors (Basel, Switzerland)
This research investigated real-time fingertip detection in frames captured from the increasingly popular wearable device, smart glasses. The egocentric-view fingertip detection and character recognition can be used to create a novel way of inputting...

Using NLP in openEHR archetypes retrieval to promote interoperability: a feasibility study in China.

BMC medical informatics and decision making
BACKGROUND: With the development and application of medical information system, semantic interoperability is essential for accurate and advanced health-related computing and electronic health record (EHR) information sharing. The openEHR approach can...

An Extended Approach to Predict Retinopathy in Diabetic Patients Using the Genetic Algorithm and Fuzzy C-Means.

BioMed research international
The present study is developed a new approach using a computer diagnostic method to diagnosing diabetic diseases with the use of fluorescein images. In doing so, this study presented the growth region algorithm for the aim of diagnosing diabetes, con...

Construction and Validation of a Lung Cancer Diagnostic Model Based on 6-Gene Methylation Frequency in Blood, Clinical Features, and Serum Tumor Markers.

Computational and mathematical methods in medicine
Lung cancer has a high mortality rate. Promoting early diagnosis and screening of lung cancer is the most effective way to enhance the survival rate of lung cancer patients. Through computer technology, a comprehensive evaluation of genetic testing r...

Detection and classification of arrhythmia using an explainable deep learning model.

Journal of electrocardiology
BACKGROUND: Early detection and intervention is the cornerstone for appropriate treatment of arrhythmia and prevention of complications and mortality. Although diverse deep learning models have been developed to detect arrhythmia, they have been crit...

Digital Death and Thanatechnology: New Ways of Thinking About Data (Im)Mortality and Digital Transformation.

Omics : a journal of integrative biology
Digital technologies such as the Internet of Things and artificial intelligence are changing how we live and do research, for example, the ways in which patient-reported outcomes and phenomics big data are curated and analyzed. Digital transformation...

Automated segmentation and quantification of the healthy and diseased aorta in CT angiographies using a dedicated deep learning approach.

European radiology
OBJECTIVES: To develop and validate a deep learning-based algorithm for segmenting and quantifying the physiological and diseased aorta in computed tomography angiographies.

Abstraction and analogy-making in artificial intelligence.

Annals of the New York Academy of Sciences
Conceptual abstraction and analogy-making are key abilities underlying humans' abilities to learn, reason, and robustly adapt their knowledge to new domains. Despite a long history of research on constructing artificial intelligence (AI) systems with...