AIMC Topic: Humans

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Health Information Seeking From an Intelligent Web-Based Symptom Checker: Cross-sectional Questionnaire Study.

Journal of medical Internet research
BACKGROUND: The ever-growing amount of health information available on the web is increasing the demand for tools providing personalized and actionable health information. Such tools include symptom checkers that provide users with a potential diagno...

Implementation of a new Digi-HTA process for digital health technologies in Finland.

International journal of technology assessment in health care
OBJECTIVES: There has been a lack of health technology assessment (HTA) methods for novel digital health technologies (DHTs) such as mHealth, artificial intelligence, and robotics in Finland. The Digi-HTA method has been developed for this purpose. T...

Deep learning reveals cuproptosis features assist in predict prognosis and guide immunotherapy in lung adenocarcinoma.

Frontiers in endocrinology
BACKGROUND: Cuproptosis is a recently found non-apoptotic cell death type that holds promise as an emerging therapeutic modality in lung adenocarcinoma (LUAD) patients who develop resistance to radiotherapy and chemotherapy. However, the Cuproptosis'...

Study on Regenerative Processing Performance of Chlorinated Polyethylene Based on Wireless Network and Artificial Intelligence Technology.

Computational intelligence and neuroscience
The development of Information Technology has intruded the chemical industry. In the conventional chemical industry, humans are involved in monitoring the chemical evaporation processes. If there is any damage, then humans suffer enormously. These dr...

Evaluation of College English Teaching Quality Based on Improved BT-SVM Algorithm.

Computational intelligence and neuroscience
With the development of teaching evaluation program, colleges and universities have reformed according to the actual situation of the school. With the development of evaluation activities, many universities are eager to establish their own teaching q...

Tooth CT Image Segmentation Method Based on the U-Net Network and Attention Module.

Computational and mathematical methods in medicine
Traditional image segmentation methods often encounter problems of low segmentation accuracy and being time-consuming when processing complex tooth Computed Tomography (CT) images. This paper proposes an improved segmentation method for tooth CT imag...

A Machine Learning Perspective on fNIRS Signal Quality Control Approaches.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Despite a rise in the use of functional Near Infra-Red Spectroscopy (fNIRS) to study neural systems, fNIRS signal processing is not standardized and is highly affected by empirical and manual procedures. At the beginning of any signal processing proc...

On the Deep Learning Models for EEG-Based Brain-Computer Interface Using Motor Imagery.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Motor imagery (MI) based brain-computer interface (BCI) is an important BCI paradigm which requires powerful classifiers. Recent development of deep learning technology has prompted considerable interest in using deep learning for classification and ...

Deep learning-based denoising in projection-domain and reconstruction-domain for low-dose myocardial perfusion SPECT.

Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
BACKGROUND: Low-dose (LD) myocardial perfusion (MP) SPECT suffers from high noise level, leading to compromised diagnostic accuracy. Here we investigated the denoising performance for MP-SPECT using a conditional generative adversarial network (cGAN)...