AIMC Topic: Humans

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Two-phase non-invasive multi-disease detection via sublingual region.

Computers in biology and medicine
Non-invasive multi-disease detection is an active technology that detects human diseases automatically. By observing images of the human body, computers can make inferences on disease detection based on artificial intelligence and computer vision tec...

CBDPS 1.0: A Python GUI Application for Machine Learning Models to Predict Bitter-Tasting Children's Oral Medicines.

Chemical & pharmaceutical bulletin
Bitter tastes are innately aversive and are thought to help protect animals from consuming poisons. Children are extremely sensitive to drug tastes, and their compliance is especially poor with bitter medicine. Therefore, judging whether a drug is bi...

I, robot: depression plays different roles in human-human and human-robot interactions.

Translational psychiatry
Socially engaging robots have been increasingly applied to alleviate depressive symptoms and to improve the quality of social life among different populations. Seeing that depression negatively influences social reward processing in everyday interact...

Deep learning assisted quantitative assessment of histopathological markers of Alzheimer's disease and cerebral amyloid angiopathy.

Acta neuropathologica communications
Traditionally, analysis of neuropathological markers in neurodegenerative diseases has relied on visual assessments of stained sections. Resulting semiquantitative scores often vary between individual raters and research centers, limiting statistical...

AttentionDDI: Siamese attention-based deep learning method for drug-drug interaction predictions.

BMC bioinformatics
BACKGROUND: Drug-drug interactions (DDIs) refer to processes triggered by the administration of two or more drugs leading to side effects beyond those observed when drugs are administered by themselves. Due to the massive number of possible drug pair...

Neural Network-Based Mapping Mining of Image Style Transfer in Big Data Systems.

Computational intelligence and neuroscience
Image style transfer can realize the mutual transfer between different styles of images and is an essential application for big data systems. The use of neural network-based image data mining technology can effectively mine the useful information in ...

Method for Diagnosis of Acute Lymphoblastic Leukemia Based on ViT-CNN Ensemble Model.

Computational intelligence and neuroscience
Acute lymphocytic leukemia (ALL) is a deadly cancer that not only affects adults but also accounts for about 25% of childhood cancers. Timely and accurate diagnosis of the cancer is an important premise for effective treatment to improve survival rat...

A 3D-2D Convolutional Neural Network and Transfer Learning for Hyperspectral Image Classification.

Computational intelligence and neuroscience
As one of the fast evolution of remote sensing and spectral imagery techniques, hyperspectral image (HSI) classification has attracted considerable attention in various fields, including land survey, resource monitoring, and among others. Nonetheless...

A New Optimal Diagnosis System for Coronavirus (COVID-19) Diagnosis Based on Archimedes Optimization Algorithm on Chest X-Ray Images.

Computational intelligence and neuroscience
The new coronavirus, COVID-19, has affected people all over the world. Coronaviruses are a large group of viruses that can infect animals and humans and cause respiratory distress; these discomforts may be as mild as a cold or as severe as pneumonia....

DeepHistoClass: A Novel Strategy for Confident Classification of Immunohistochemistry Images Using Deep Learning.

Molecular & cellular proteomics : MCP
A multitude of efforts worldwide aim to create a single-cell reference map of the human body, for fundamental understanding of human health, molecular medicine, and targeted treatment. Antibody-based proteomics using immunohistochemistry (IHC) has pr...