AIMC Topic: Algorithms

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Segmentation of gastroesophageal reflux events using a semi-U-Net architecture with 1D/2D CNNs.

Scientific reports
U-Net has gained traction in biomedical signal processing, particularly for segmenting 1D waveforms. Building on this success, we propose a U-Net-inspired architecture that integrates both 2D and 1D CNNs to effectively learn and segment gastroesophag...

A multi stage deep learning model for accurate segmentation and classification of breast lesions in mammography.

Scientific reports
Mammography is a routine imaging technique used by radiologists to detect breast lesions, such as tumors and lumps. Precise lesion detection is critical for early treatment and diagnosis planning. Lesion detection and segmentation are still problemat...

Optimizing YOLOv11 for automated classification of breast cancer in medical images.

Scientific reports
Breast cancer diagnosis via histopathology image analysis is a complex and subjective process. While deep learning has emerged as a powerful tool for automation, achieving high accuracy across diverse cancer subtypes and magnification levels remains ...

Fine-scale predictive modeling of Aedes mosquito abundance and dengue risk indicators using machine learning algorithms with microclimatic variables.

Scientific reports
Effective prediction of Aedes mosquito abundance and dengue risk indicators such as the Aedes Index (AI) and Dengue Positive Trap Index (DPTI) is essential for early intervention and targeted vector control. However, current models often rely on coar...

Digital Twins for Monitoring Neuromotor Development in Preterm Infants: Conceptual Framework and Proof-of-concept Study.

Journal of medical systems
Preterm birth leads to an increased risk of long-term consequences, with over 50% of children born <30 weeks facing motor, cognitive, or behavioural impairments. Early monitoring of motor developmental trajectories, strongly associated with neurodeve...

Cardiovascular risk prediction in diabetes: a hybrid machine learning approach.

Biomedical physics & engineering express
Cardiovascular disease (CVD) is a major cause of morbidity and mortality in diabetic populations. Early detection of cardiovascular risk in diabetes is crucial to reduce complications, particularly in resource-limited settings. This study aimed to de...

The apple detection method based on multimodal features.

PloS one
Accurate detection of apples and other fruits in complex environments remains a formidable challenge due to the intricate interplay of varying lighting conditions, occlusions, and background clutter. Traditional detection methods, which primarily rel...

Neural subgraph counting on stream graphs via localized updates and monotonic learning.

PloS one
Graphs are a representative type of fundamental data structures. They are capable of representing complex association relationships in diverse domains. For large-scale graph processing, the stream graphs have become efficient tools to process dynamic...

Contrastive learning-enhanced personalized interaction dual tower network for recommendation.

PloS one
Dual-tower retrieval models have become a prevalent solution in large-scale recommendation systems due to their scalability and deployment efficiency. However, they face critical limitations including insufficient modeling of user behavior sequences,...

Identification and velocity measurement of microplastics based on machine learning.

Water research
The settling velocity of microplastics (MPs) is a critical parameter for understanding their migration and behavior in aquatic environments. Conventional methods typically focus on tracking individual MPs and often face significant challenges in capt...