AIMC Topic: Humans

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Artificial intelligence-integrated video analysis of vessel area changes and instrument motion for microsurgical skill assessment.

Scientific reports
Mastering microsurgical skills is essential for neurosurgical trainees. Video-based analysis of target tissue changes and surgical instrument motion provides an objective, quantitative method for assessing microsurgical proficiency, potentially enhan...

Bind: large-scale biological interaction network discovery through knowledge graph-driven machine learning.

Journal of translational medicine
BACKGROUND: Biological systems derive from complex interactions between entities ranging from biomolecules to macroscopic structures, forming intricate networks essential for understanding disease mechanisms and developing therapeutic interventions. ...

Impact of large language models and vision deep learning models in predicting neoadjuvant rectal score for rectal cancer treated with neoadjuvant chemoradiation.

BMC medical imaging
This study aims to explore Deep Learning methods, namely Large Language Models (LLMs) and Computer Vision models to accurately predict neoadjuvant rectal (NAR) score for locally advanced rectal cancer (LARC) treated with neoadjuvant chemoradiation (N...

Uncovering active ingredients and mechanisms of Pholiota adiposa in the treatment of Alzheimer's disease based on network pharmacology and bioinformatics.

Scientific reports
Pholiota adiposa is recognized for its health benefits, particularly in Alzheimer's disease (AD), but its molecular mechanism remains elusive. Our study employs network pharmacology and machine learning to uncover its therapeutic potential. We constr...

Integrated transcriptomic and functional modeling reveals AKT and mTOR synergy in colorectal cancer.

Scientific reports
Colorectal cancer (CRC) treatment remains challenging due to genetic heterogeneity and resistance mechanisms. To address this, we developed a drug discovery pipeline using patient-derived primary CRC cultures with diverse genomic profiles. These cult...

Predicting stunting status among under five children in ethiopia using ensemblemachine learning algorithms.

Scientific reports
Childhood stunting is a persistent public health challenge in Ethiopia, significantly impacting children's physical growth, cognitive development, and overall well-being. This study overcame a key limitation in previous stunting prediction models by ...

A dataset for recognition of Arabic accents from spoken L2 English speech (ArL2Eng).

Scientific data
This paper introduces the ArL2Eng dataset, a speech corpus of L2 English produced by native speakers of Arabic, and highlights its potential in supporting research into automated language assessment. ArL2Eng comprises audio sequences from speakers of...

Investigating the Impact of the Stationarity Hypothesis on Heart Failure Detection using Deep Convolutional Scattering Networks and Machine Learning.

Scientific reports
Detection of Cardiovascular Diseases (CVDs) has become crucial nowadays, as the World Health Organization (WHO) declares CVDs as the major leading causes of death in the globe. Moreover, the death rate due to CVDs is expected to rise in the next few ...

Advancing deep learning for expressive music composition and performance modeling.

Scientific reports
The pursuit of expressive and human-like music generation remains a significant challenge in the field of artificial intelligence (AI). While deep learning has advanced AI music composition and transcription, current models often struggle with long-t...

Integrative network pharmacology and multi-omics reveal anisodamine hydrobromide's multi-target mechanisms in sepsis.

Scientific reports
Sepsis, marked by hyperinflammation and subsequent immunosuppression, lacks effective phase-specific therapies. Although anisodamine hydrobromide (Ani HBr) reduced 28-day mortality in our prior trial, its mechanisms remained unclear. Here, we integra...