AIMC Topic: Humans

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Early diagnostic biomarkers for acute myocardial infarction unveiled by metabolomics, Mendelian randomization, and machine learning.

Molecular biomedicine
Acute myocardial infarction (AMI) remains a leading cause of global cardiovascular morbidity and mortality. Limitations in current diagnostic methods hinder early detection and intervention, creating an urgent need for novel early diagnostic biomarke...

Deep source separation for single-channel fetal ECG extraction.

Physiological measurement
the fetal electrocardiogram (FECG) is critical for monitoring fetal health, however, its extraction remains technically challenging due to strong interference from the maternal electrocardiogram (MECG) in abdominal electrocardiogram (AECG). Therefore...

Large Language Models for Psychiatric Diagnosis Based on Multicenter Real-World Clinical Records: Comparative Study.

JMIR medical informatics
BACKGROUND: Psychiatric disorders are diagnostically challenging and often rely on subjective clinical judgment, particularly in resource-limited settings. Large language models (LLMs) have demonstrated potential in supporting psychiatric diagnosis; ...

Interpretable deep learning for enhanced multi-class classification of gastrointestinal endoscopic images.

Biomedical physics & engineering express
Gastrointestinal (GI) endoscopy serves as a vital tool for assessing the GI tract and diagnosing related disorders. Recent progress in deep learning has shown significant improvements in identifying anomalies using sophisticated models and data augme...

Peptide-based drug design using generative AI.

Chemical communications (Cambridge, England)
Peptide-based therapeutics have emerged as a significant treatment strategy, offering high specificity and tunable pharmacokinetics. Recent advances in Artificial Intelligence (AI) have shifted the focus towards structure prediction, generative desig...

Nanobodies targeting ion channels: advancing therapeutics through precision and structural insights.

Chemical communications (Cambridge, England)
Ion channels, which are integral to cellular signaling and homeostasis, are implicated in a variety of diseases, including neurological disorders, cardiovascular conditions, and cancers. Despite their importance, targeting ion channels therapeuticall...

CTA-based deep-learning integrated model for identifying irregular shape and aneurysm size of unruptured intracranial aneurysms.

Journal of neurointerventional surgery
BACKGROUND: Artificial intelligence can help to identify irregular shapes and sizes, crucial for managing unruptured intracranial aneurysms (UIAs). However, existing artificial intelligence tools lack reliable classification of UIA shape irregularity...

Predicting symptomatic intracranial hemorrhage after endovascular treatment of vertebrobasilar artery occlusion: PEACE score.

Journal of neurointerventional surgery
BACKGROUND: Current clinical decision tools for assessing the risk of symptomatic intracranial hemorrhage (sICH) in patients with vertebrobasilar artery occlusion (VBAO) who received endovascular treatment (EVT) have limited performance. This study d...

Workflow improvements from automated large vessel occlusion detection algorithms are dependent on care team engagement.

Journal of neurointerventional surgery
BACKGROUND: Automated machine learning (ML)-based large vessel occlusion (LVO) detection algorithms have been shown to improve in-hospital workflow metrics including door-to-groin time (DTG). The degree to which care team engagement and interaction a...

RUL prediction method based on sequential health index evaluation with multidimensional coupled degradation data.

PloS one
Remaining Useful Life (RUL) prediction is crucial for implementing predictive maintenance strategies, however, RUL prediction is severely constrained by the lack of high-quality labeled life-cycle data. Moreover, complex coupling relationships exist ...