AIMC Topic: Algorithms

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An advanced skin lesion segmentation and classification framework using deep learning strategies.

Scientific reports
Skin cancer is a deadly kind of cancer that grows rapidly and produces life-threatening issues within six weeks from the initial stage. Accurate analysis is needed for observing both the malignant and benign skin lesions that are more complicated to ...

Automatic detection of harmful cyanobacterial genera using deep CNN models and artemisinin optimization.

Scientific reports
Concerns over the spread of Cyanobacteria, which can lead to dangerous blooms that harm drinking water quality and, therefore, the health of plants and animals, are being raised by global warming. Traditional methods for assessing the amount of toxic...

Enhanced EfficientNet-Extended Multimodal Parkinson's disease classification with Hybrid Particle Swarm and Grey Wolf Optimizer.

Scientific reports
Parkinson's disease (PD) is a chronic neurodegenerative disorder characterized by progressive loss of dopaminergic neurons in substantia nigra, resulting in both motor impairments and cognitive decline. Traditional PD classification methods are exper...

SARST2 high-throughput and resource-efficient protein structure alignment against massive databases.

Nature communications
The flood of protein structural Big Data is coming. With the belief that biotech researchers deserve powerful analysis engines to overcome the challenge of rapidly increasing computational demands, we are devoted to developing efficient protein struc...

TFDISNet: Temporal-frequency domain-invariant and domain-specific feature learning network for enhanced auditory attention decoding from EEG signals.

Biomedical physics & engineering express
Auditory Attention Decoding (AAD) from Electroencephalogram (EEG) signals presents a significant challenge in brain-computer interface (BCI) research due to the intricate nature of neural patterns. Existing approaches often fail to effectively integr...

Surrogate modeling for time-dependent reliability analysis of robotic manipulator trajectories.

PloS one
The kinematic reliability analysis of robotic manipulators is crucial due to uncertainties such as joint variations, manufacturing tolerances, and external disturbances. Traditional methods often rely on analytical techniques that struggle with nonli...

An efficient deep learning network for brain stroke detection using salp shuffled shepherded optimization.

Scientific reports
Brain strokes (BS) are potentially life-threatening cerebrovascular conditions and the second highest contributor to mortality. They include hemorrhagic and ischemic strokes, which vary greatly in size, shape, and location, posing significant challen...

Deep learning model for diagnosing lupus erythematosus in cardiac patients using ECG and audio spectrograms.

Scientific reports
Individuals with both Lupus Erythematosus and pre-existing heart conditions are more likely to develop severe symptoms, emphasizing the complex and not fully understood interaction between the disease and cardiovascular health. A universal diagnostic...

A comprehensive application of FiveFold for conformation ensemble-based protein structure prediction.

Scientific reports
The emergence of artificial intelligence in protein structure prediction has significantly advanced our understanding of protein folding. Yet, challenges remain in accurately modeling intrinsically disordered proteins (IDPs) and capturing conformatio...

An infection prediction model developed from inpatient data can predict out-of-hospital COVID-19 infections from wearable data when controlled for dataset shift.

Scientific reports
The COVID-19 pandemic highlighted the importance of early detection of illness and the need for health monitoring solutions outside of the hospital setting. We have previously demonstrated a real-time system to identify COVID-19 infection before diag...