AIMC Topic: Algorithms

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Property Prediction for Complex Compounds Using Structure-Free Mendeleev Encoding and Machine Learning.

Journal of chemical information and modeling
Predicting the properties for unseen materials exclusively on the basis of the chemical formula before synthesis and characterization has advantages for research and resource planning. This can be achieved using suitable structure-free encoding and m...

Semantically-Enhanced Feature Extraction with CLIP and Transformer Networks for Driver Fatigue Detection.

Sensors (Basel, Switzerland)
Drowsy driving is a leading cause of commercial vehicle traffic crashes. The trend is to train fatigue detection models using deep neural networks on driver video data, but challenges remain in coarse and incomplete high-level feature extraction and ...

Acute kidney disease in hospitalized pediatric patients: risk prediction based on an artificial intelligence approach.

Renal failure
BACKGROUND: Acute kidney injury (AKI) and acute kidney disease (AKD) are prevalent among pediatric patients, both linked to increased mortality and extended hospital stays. Early detection of kidney injury is crucial for improving outcomes. This stud...

Integration of biological data via NMF for identification of human disease-associated gene modules through multi-label classification.

PloS one
Proteins associated with multiple diseases often interact, forming disease modules that are critical for understanding disease mechanisms. This study integrates protein-protein interactions (PPIs) and Gene Ontology data using non-negative matrix fact...

PHyPO: Priority-based Hybrid task Partitioning and Offloading in mobile computing using automated machine learning.

PloS one
With the increasing demand for mobile computing, the requirement for intelligent resource management has also increased. Cloud computing lessens the energy consumption of user equipment, but it increases the latency of the system. Whereas edge comput...

VIIDA and InViDe: computational approaches for generating and evaluating inclusive image paragraphs for the visually impaired.

Disability and rehabilitation. Assistive technology
BACKGROUND: Existing image description methods when used as Assistive Technologies often fall short in meeting the needs of blind or low vision (BLV) individuals. They tend to either compress all visual elements into brief captions, create disjointed...

Cluster synchronization of fractional-order two-layer networks and application in image encryption/decryption.

Neural networks : the official journal of the International Neural Network Society
In this paper, a type of fractional-order two-layer network model is constructed, wherein each layer in the network exhibits distinct topology. Subsequently, the cluster synchronization problem of fractional-order two-layer networks is investigated t...

DeepPD: A Deep Learning Method for Predicting Peptide Detectability Based on Multi-feature Representation and Information Bottleneck.

Interdisciplinary sciences, computational life sciences
Peptide detectability measures the relationship between the protein composition and abundance in the sample and the peptides identified during the analytical procedure. This relationship has significant implications for the fundamental tasks of prote...

Residual risk prediction in anticoagulated patients with atrial fibrillation using machine learning: A report from the GLORIA-AF registry phase II/III.

European journal of clinical investigation
BACKGROUND: Although oral anticoagulation decreases the risk of thromboembolism in patients with atrial fibrillation (AF), a residual risk of thrombotic events still exists. This study aimed to construct machine learning (ML) models to predict the re...