AIMC Topic: Humans

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Predicting the Reparability of Rotator Cuff Tears: Machine Learning and Comparison With Previous Scoring Systems.

The American journal of sports medicine
BACKGROUND: Repair of rotator cuff tear is not always feasible, depending on the severity. Although several studies have investigated factors related to reparability and various methods to predict it, inconsistent scoring methods and a lack of valida...

NFSA-DTI: A Novel Drug-Target Interaction Prediction Model Using Neural Fingerprint and Self-Attention Mechanism.

International journal of molecular sciences
Existing deep learning methods have shown outstanding performance in predicting drug-target interactions. However, they still have limitations: (1) the over-reliance on locally extracted features by some single encoders, with insufficient considerati...

An Accurate and Efficient Approach to Knowledge Extraction from Scientific Publications Using Structured Ontology Models, Graph Neural Networks, and Large Language Models.

International journal of molecular sciences
The rapid growth of biomedical literature makes it challenging for researchers to stay current. Integrating knowledge from various sources is crucial for studying complex biological systems. Traditional text-mining methods often have limited accuracy...

Quantification of Size-Binned Particulate Matter in Electronic Cigarette Aerosols Using Multi-Spectral Optical Sensing and Machine Learning.

Sensors (Basel, Switzerland)
To monitor health risks associated with vaping, we introduce a multi-spectral optical sensor powered by machine learning for real-time characterization of electronic cigarette aerosols. The sensor can accurately measure the mass of particulate matter...

Two-Stream Modality-Based Deep Learning Approach for Enhanced Two-Person Human Interaction Recognition in Videos.

Sensors (Basel, Switzerland)
Human interaction recognition (HIR) between two people in videos is a critical field in computer vision and pattern recognition, aimed at identifying and understanding human interaction and actions for applications such as healthcare, surveillance, a...

Identification of novel hypertension biomarkers using explainable AI and metabolomics.

Metabolomics : Official journal of the Metabolomic Society
BACKGROUND: The global incidence of hypertension, a condition of elevated blood pressure, is rising alarmingly. According to the World Health Organization's Qatar Hypertension Profile for 2023, around 33% of adults are affected by hypertension. This ...

Multimodal AI/ML for discovering novel biomarkers and predicting disease using multi-omics profiles of patients with cardiovascular diseases.

Scientific reports
Cardiovascular diseases (CVDs) are complex, multifactorial conditions that require personalized assessment and treatment. Advancements in multi-omics technologies, namely RNA sequencing and whole-genome sequencing, have provided translational researc...

Novel large empirical study of deep transfer learning for COVID-19 classification based on CT and X-ray images.

Scientific reports
The early and highly accurate prediction of COVID-19 based on medical images can speed up the diagnostic process and thereby mitigate disease spread; therefore, developing AI-based models is an inevitable endeavor. The presented work, to our knowledg...

Co-Mask R-CNN: collaborative learning-based method for tooth instance segmentation.

The Journal of clinical pediatric dentistry
Traditional tooth image analysis methods primarily focus on feature extraction from individual images, often overlooking critical tooth shape and position information. This paper presents a novel computer-aided diagnosis method, Collaborative learnin...