AIMC Topic: Algorithms

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An artificial intelligence-based recognition model of colorectal liver metastases in intraoperative ultrasonography with improved accuracy through algorithm integration.

Journal of hepato-biliary-pancreatic sciences
BACKGROUND/PURPOSE: Contrast-enhanced intraoperative ultrasonography (CE-IOUS) is crucial for detecting colorectal liver metastases (CLM) during surgery. Although artificial intelligence shows potential in diagnostic systems, its application in CE-IO...

The use of 4D data-independent acquisition-based proteomic analysis and machine learning to reveal potential biomarkers for stress levels.

Journal of bioinformatics and computational biology
Research suggests that individuals who experience prolonged exposure to stress may be at higher risk for developing psychological stress disorders. Currently, psychological stress is primarily evaluated by professional physicians using rating scales,...

Partial prior transfer learning based on self-attention CNN for EEG decoding in stroke patients.

Scientific reports
The utilization of motor imagery-based brain-computer interfaces (MI-BCI) has been shown to assist stroke patients activate motor regions in the brain. In particular, the brain regions activated by unilateral upper limb multi-task are more extensive,...

Optimized robust learning framework based on big data for forecasting cardiovascular crises.

Scientific reports
Numerous Deep Learning (DL) scenarios have been developed for evolving new healthcare systems that leverage large datasets, distributed computing, and the Internet of Things (IoT). However, the data used in these scenarios tend to be noisy, necessita...

Machine learning, healthcare resource allocation, and patient consent.

The New bioethics : a multidisciplinary journal of biotechnology and the body
The impact of machine learning in healthcare on patient informed consent is now the subject of significant inquiry in bioethics. However, the topic has predominantly been considered in the context of black box diagnostic or treatment recommendation a...

Sex prediction through machine learning utilizing mandibular condyles, coronoid processes, and sigmoid notches features.

PloS one
Characteristics of the mandible structures have been relevant in anthropological and forensic studies for sex prediction. This study aims to evaluate the coronoid process, condyle, and sigmoid notch patterns in sex prediction through supervised machi...

MaskDGNets: Masked-attention guided dynamic graph aggregation network for event extraction.

PloS one
Considering that the traditional deep learning event extraction method ignores the correlation between word features and sequence information, it cannot fully explore the hidden associations between events and events and between events and primary at...

AFSleepNet: Attention-Based Multi-View Feature Fusion Framework for Pediatric Sleep Staging.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
The widespread prevalence of sleep problems in children highlights the importance of timely and accurate sleep staging in the diagnosis and treatment of pediatric sleep disorders. However, most existing sleep staging methods rely on one-dimensional r...

Predicting Protein-Ligand Binding Affinity Using Fusion Model of Spatial-Temporal Graph Neural Network and 3D Structure-Based Complex Graph.

Interdisciplinary sciences, computational life sciences
The investigation of molecular interactions between ligands and their target molecules is becoming more significant as protein structure data continues to develop. In this study, we introduce PLA-STGCNnet, a deep fusion spatial-temporal graph neural ...