AIMC Topic: Humans

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Application of deep learning methods: From molecular modelling to patient classification.

Experimental cell research
We are now well into the information driven age with complex, heterogeneous, datasets in the biological sciences continuing to grow at a rapid pace. Moreover, distilling of such datasets, to find new governing principles, are underway. Leading the su...

EEG based depression recognition using improved graph convolutional neural network.

Computers in biology and medicine
Depression is a global psychological disease that does serious harm to people. Traditional diagnostic method of the doctor-patient communication, is not objective and accurate enough. Thus, a more accurate and objective method for depression detectio...

Determination gender-based hybrid artificial intelligence of body muscle percentage by photoplethysmography signal.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Muscle mass is one of the critical components that ensure muscle function. Loss of muscle mass at every stage of life can cause many adverse effects. Sarcopenia, which can occur in different age groups and is characterized b...

SAFNet: A deep spatial attention network with classifier fusion for breast cancer detection.

Computers in biology and medicine
Breast cancer is a top dangerous killer for women. An accurate early diagnosis of breast cancer is the primary step for treatment. A novel breast cancer detection model called SAFNet is proposed based on ultrasound images and deep learning. We employ...

Utility of artificial intelligence with deep learning of hematoxylin and eosin-stained whole slide images to predict lymph node metastasis in T1 colorectal cancer using endoscopically resected specimens; prediction of lymph node metastasis in T1 colorectal cancer.

Journal of gastroenterology
BACKGROUND: When endoscopically resected specimens of early colorectal cancerĀ (CRC) show high-risk features, surgery should be performed based on current guidelines because of the high-risk of lymph node metastasis (LNM). The aim of this study was to...

Trustworthy assertion classification through prompting.

Journal of biomedical informatics
Accurate identification of the presence, absence or possibility of relevant entities in clinical notes is important for healthcare professionals to quickly understand crucial clinical information. This introduces the task of assertion classification ...

DRSNFuse: Deep Residual Shrinkage Network for Infrared and Visible Image Fusion.

Sensors (Basel, Switzerland)
Infrared images are robust against illumination variation and disguises, containing the sharp edge contours of objects. Visible images are enriched with texture details. Infrared and visible image fusion seeks to obtain high-quality images, keeping t...

Cardiotocography in Obstetrics: New Solutions for "Routine" Technology.

Sensors (Basel, Switzerland)
This work is devoted to the problems of one of the most common screening examinations used in medical practice: fetal cardiotocography (CTG). The technology of ultrasonic monitoring of fetal heart rate (HR) variations has been used for more than 70 y...

Exploring the Chinese Public's Perception of Omicron Variants on Social Media: LDA-Based Topic Modeling and Sentiment Analysis.

International journal of environmental research and public health
The COVID-19 pandemic caused by SARS-CoV-2 is still raging. Similar to other RNA viruses, SARS-COV-2 is constantly mutating, which leads to the production of many infectious and lethal strains. For instance, the omicron variant detected in November 2...

Dental anomaly detection using intraoral photos via deep learning.

Scientific reports
Children with orofacial clefting (OFC) present with a wide range of dental anomalies. Identifying these anomalies is vital to understand their etiology and to discern the complex phenotypic spectrum of OFC. Such anomalies are currently identified usi...