AIMC Topic: Humans

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Two-factor synaptic consolidation reconciles robustness with pruning and homeostatic scaling.

Proceedings of the National Academy of Sciences of the United States of America
Memory consolidation refers to a process of engram reorganization and stabilization that is thought to occur primarily during sleep through a combination of neural replay, homeostatic plasticity, synaptic maturation, and pruning. From a computational...

Primary tumor resection: a new hope or an old illusion for patients with metastatic non-small cell lung neuroendocrine tumors?

World journal of surgical oncology
OBJECTIVES: This study aimed to investigate the impact of primary tumor resection (PTR) on survival outcomes for patients with metastatic non-small cell neuroendocrine tumors (mNSCLC-NETs), develop a predictive model to identify which patients may be...

Spatial-reprogramming derived GPNMB macrophages interact with COL6A3 fibroblasts to enhance vascular fibrosis in glioblastoma.

Genome medicine
BACKGROUND: Neoadjuvant therapy plays an important role in the treatment of glioblastoma (GBM), but a considerable proportion of patients remain unresponsive to the combination of immune checkpoint blockade (ICB) and antiangiogenic therapy. Understan...

Clinician-in-the-loop screening saturation: predicting annotation yield for efficient EHR review.

BMC medical informatics and decision making
BACKGROUND: Labor- and cost-intensive manual chart review of Electronic Health Records (EHRs) remains a major bottleneck in retrospective studies, particularly when rare-disease cohorts require high specificity. Automated Natural Language Processing ...

A machine learning model including pentraxin-3 as predictor of outcomes in community-acquired pneumonia.

Journal of translational medicine
BACKGROUND: The clinical diagnosis, severity assessment, and outcome prognostication of community-acquired pneumonia (CAP) remain challenging due to the complex disease pathophysiology. Accurate outcome prediction is crucial for optimizing patient ma...

Skel-Net: automatic prediction of skeletal pattern on scanned lateral cephalograms using anatomical prior-guided deep learning network.

BMC oral health
BACKGROUND: Estimating craniofacial patterns is essential for successful orthodontic treatment. However, conventional static measurements are inadequate for capturing dynamic changes, and manual cephalometric analysis is labor-intensive and requires ...

Functionalized mesenchymal stem cells for enhanced bone regeneration: advances and challenges.

Stem cell research & therapy
Bone fracture continues to pose a significant clinical challenge in regenerative medicine due to limited repair capacity and inadequate therapeutic options. Among the various therapeutic strategies, mesenchymal stem cells have shown strong potential ...

An MRI-based radiomics framework for early identification and progression stratification in knee osteoarthritis: data from the osteoarthritis initiative.

BMC musculoskeletal disorders
OBJECTIVES: To develop a cascaded machine learning model based on MRI radiomics features from cartilage and subchondral bone to predict the incidence and progression of knee osteoarthritis (KOA), thereby addressing the need for early intervention in ...

Joint explainable and fair AI in healthcare.

BMC medical informatics and decision making
The nature of decisions in the healthcare domain necessitates accurate, interpretable, and reliable AI solutions. Explanation Guided Learning (EGL) explores the integration of explanation annotations into learning models to align human and model expl...

Factors associated with allergic diseases in Chinese children aged 6-14 years.

BMC public health
BACKGROUND AND OBJECTIVES: We aimed to identify and optimize contributing factors associated with allergic diseases by machine/deep learning algorithms among school-age children aged 6-14 years.