AIMC Topic: Humans

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Classifying breast cancer subtypes on multi-omics data via sparse canonical correlation analysis and deep learning.

BMC bioinformatics
BACKGROUND: Classifying breast cancer subtypes is crucial for clinical diagnosis and treatment. However, the early symptoms of breast cancer may not be apparent. Rapid advances in high-throughput sequencing technology have led to generating large num...

Employing deep learning and transfer learning for accurate brain tumor detection.

Scientific reports
Artificial intelligence-powered deep learning methods are being used to diagnose brain tumors with high accuracy, owing to their ability to process large amounts of data. Magnetic resonance imaging stands as the gold standard for brain tumor diagnosi...

Automated analysis of knee joint alignment using detailed angular values in long leg radiographs based on deep learning.

Scientific reports
Malalignment in the lower limb structure occurs due to various causes. Accurately evaluating limb alignment in situations where malalignment needs correction is necessary. To create an automated support system to evaluate lower limb alignment by quan...

Teaching robots the art of human social synchrony.

Science robotics
Humanoid robots can now learn the art of social synchrony using neural networks.

Human-robot facial coexpression.

Science robotics
Large language models are enabling rapid progress in robotic verbal communication, but nonverbal communication is not keeping pace. Physical humanoid robots struggle to express and communicate using facial movement, relying primarily on voice. The ch...

Towards the adoption of quantitative computed tomography in the management of interstitial lung disease.

European respiratory review : an official journal of the European Respiratory Society
The shortcomings of qualitative visual assessment have led to the development of computer-based tools to characterise and quantify disease on high-resolution computed tomography (HRCT) in patients with interstitial lung diseases (ILDs). Quantitative ...

GraphMHC: Neoantigen prediction model applying the graph neural network to molecular structure.

PloS one
Neoantigens are tumor-derived peptides and are biomarkers that can predict prognosis related to immune checkpoint inhibition by estimating their binding to major histocompatibility complex (MHC) proteins. Although deep neural networks have been prima...

Powerful tool or too powerful? Early public discourse about ChatGPT across 4 million tweets.

PloS one
BACKGROUND: This paper investigates initial exuberance and emotions surrounding ChatGPT's first three months of launch (1 December 2022-1 March 2023). The impetus for studying active discussions surrounding its implications, fears, and opinions is mo...

A machine learning based depression screening framework using temporal domain features of the electroencephalography signals.

PloS one
Depression is a serious mental health disorder affecting millions of individuals worldwide. Timely and precise recognition of depression is vital for appropriate mediation and effective treatment. Electroencephalography (EEG) has surfaced as a promis...

A Review of Intelligent Walking Support Robots: Aiding Sit-to-Stand Transition and Walking.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Nowadays, numerous countries are facing the challenge of aging population. Additionally, the number of people with reduced mobility due to physical illness is increasing. In response to this issue, robots used for walking assistance and sit-to-stand ...