AIMC Topic: Deep Learning

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Deep ensemble learning with transformer models for enhanced Alzheimer's disease detection.

Scientific reports
The progression of Alzheimer's disease is relentless, leading to a worsening of mental faculties over time. Currently, there is no remedy for this illness. Accurate detection and prompt intervention are pivotal in mitigating the progression of the di...

Integrating deep learning in stride-to-stride muscle activity estimation of young and old adults with wearable inertial measurement units.

Scientific reports
Deep learning has become powerful and yet versatile tool that allows for the extraction of complex patterns from rich datasets. One field that can benefits from this advancement is human gait analysis. Conventional gait analysis requires a specialize...

A hybrid deep learning model EfficientNet with GRU for breast cancer detection from histopathology images.

Scientific reports
Breast cancer remains a significant global health challenge among women, with histopathological image analysis playing a critical role in early detection. However, existing diagnostic models often struggle to extract complex patterns from high-resolu...

Evolving Blood Pressure Estimation: From Feature Analysis to Image-Based Deep Learning Models.

Journal of medical systems
Traditional cuffless blood pressure (BP) estimation methods often require collecting physiological signals, such as electrocardiogram (ECG) and photoplethysmography (PPG), from two distinct body sites to compute metrics like pulse transit time (PTT) ...

ColoViT: a synergistic integration of EfficientNet and vision transformers for advanced colon cancer detection.

Journal of cancer research and clinical oncology
BACKGROUND: Colon cancer remains a leading cause of cancer-related mortality globally, highlighting the urgent need for advanced diagnostic methods to improve early detection and patient outcomes.

Multiparameter MRI-based automatic segmentation and diagnostic models for the differentiation of intracranial solitary fibrous tumors and meningiomas.

Annals of medicine
BACKGROUND: Intracranial solitary fibrous tumors (SFTs) and meningiomas are meningeal tumors with different malignancy levels and prognoses. Their similar imaging features make preoperative differentiation difficult, resulting in high misdiagnosis ra...

TTI and pH-responsive dual colorimetric sensor arrays combined with a cascaded deep learning approach for dynamic monitoring of freshness of fresh-cut fruits.

Food chemistry
Dynamic shelf-life monitoring of fresh-cut fruits faces challenges from temperature fluctuations and packaging failures in cold chains, causing discrepancies between theoretical predictions and actual spoilage. This study developed a dual colorimetri...

Prediction of water quality parameters and pollution exceedance analysis in typical rivers of semi-arid regions based on interpretable deep learning models.

Environmental pollution (Barking, Essex : 1987)
Deep learning models that integrate environmental characteristics provide a powerful means for high-precision water quality prediction; however, their black-box nature can limit interpretability and reliability. We proposed an interpretable Attention...

Deep Learning in Antimicrobial Peptide Prediction.

Journal of chemical information and modeling
Antimicrobial peptides (AMPs) have garnered significant attention from researchers as effective alternatives to antibiotics. In recent years, deep learning has demonstrated unique advantages in AMP prediction, surpassing traditional machine learning ...