AIMC Topic: Neural Networks, Computer

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Integrating AI-based neural network modeling with experimental characterization for Cd(II) ion adsorption using Sargassum fusiforme biosorbent.

Environmental research
Cadmium (Cd) contamination in wastewater presents serious environmental and public health challenges, requiring efficient mitigation strategies. This research focuses on assessing the biosorption capability of Sargassum fusiforme (SF) biosorbent for ...

Segmenting beyond the imaging data: creation of anatomically valid edentulous mandibular geometries for surgical planning using artificial intelligence.

Clinical oral investigations
BACKGROUND AND OBJECTIVES: Mandibular reconstruction following continuity resection due to tumor ablation or osteonecrosis remains a significant challenge in maxillofacial surgery. Virtual surgical planning (VSP) relies on accurate segmentation of th...

GLA-Synergy: An Interpretable Global-Local Adaptive Framework for Drug Synergy Prediction in Cancer Treatment.

Journal of chemical information and modeling
Effective anticancer drug combinations are crucial for advancing cancer treatment, yet predicting drug synergy remains challenging due to the complexity of biological interactions. Existing methods struggle to integrate multimodal features and to mod...

Deep Learning-Aided Noninvasive Monitoring of Skin Tissue Temperature Distribution and Blood Perfusion Rate Based on Fractal Conformal Sensors.

ACS sensors
Skin thermophysical properties are key for health assessment with real-time monitoring enabling early detection of skin-related issues. A polydimethylsiloxane-encapsulated Peano fractal conformal sensor is fabricated by flexible printed circuit techn...

Conventional and hybrid time series models for forecasting medication dispensing and errors integration in automated dispensing cabinets.

Scientific reports
Automated dispensing cabinets (ADCs) represent a critical innovation in modern healthcare, revolutionizing medication management by improving efficiency, accuracy, and security. With the increasing reliance on these technologies, optimizing their per...

Machine learning analysis of coagulation-related genes for breast cancer diagnosis and prognosis prediction.

Scientific reports
The purpose of this study was to investigate the relationship between coagulation related genes (CRGs) and breast cancer (BC). First, we found that most CRGs are abnormally expressed in BC patients and correlated with their prognosis. Therefore, we e...

Temporal recurrence as a general mechanism to explain neural responses in the auditory system.

Communications biology
Computational models of neural processing in the auditory cortex usually ignore that neurons have an internal memory: they characterize their responses from simple convolutions with a finite temporal window. To circumvent this limitation, we propose ...

Identification and validation of cell senescence genes in recurrent spontaneous abortion via multiple bioinformatics algorithms.

Scientific reports
Recurrent spontaneous abortion (RSA) represents a significant challenge in reproductive obstetrics, affecting approximately 5% of couples globally. Despite various treatments, the effectiveness of these interventions remains highly contentious. Emerg...

Transformer-assisted broad learning for hybrid intelligence-based skin cancer segmentation.

Scientific reports
With the rise of Transformer architectures, deep learning applications have gradually shifted from traditional convolutional neural networks to Transformers based on self-attention mechanisms. In tasks such as image classification, segmentation, and ...

Machine learning model to classify chronic leg wounds and identify pyoderma gangrenosum.

BMJ health & care informatics
STUDY OBJECTIVES: Chronic wounds represent a significant economic and personal burden. For their successful treatment, the causes must be known and treated. Wounds caused by pyoderma gangrenosum (PG), a rare inflammatory skin disease, are often misdi...