Latest AI and machine learning research in product alert for healthcare professionals.
Post-hoc explanation methods provide interpretation by attributing predictions to input features. ...
Deep learning-based electrocardiogram (ECG) classification has shown impressive performance but cl...
In many medical imaging tasks, convolutional neural networks (CNNs) efficiently extract local feat...
This study addresses the challenge of predicting post-stroke rigidity by emphasizing feature inter...
Convolutional neural networks (CNNs) for time series classification (TSC) are being increasingly u...
Deep learning has been successfully applied to medical image segmentation, enabling accurate ident...
Social media is a rich source of real-world data that captures valuable patient experience informa...
While most modern machine learning methods offer speed and accuracy, few promise interpretability ...
Accurate medical symptom coding from unstructured clinical text, such as vaccine safety reports, i...
Accurate segmentation of polyps and skin lesions is essential for diagnosing colorectal and skin c...
Remote tracking systems play a critical role in applications such as IoT, monitoring, surveillance...
Existing hardware-aware NAS (HW-NAS) methods typically assume access to precise information circa ...
The practice of pharmacovigilance relies on large databases of individual case safety reports to d...
Early and accurate diagnosis of pulmonary hypertension (PH) is essential for optimal patient manag...
Code translation migrates codebases across programming languages. Recently, large language models ...
Semantic similarity measures (SSMs) are widely used in biomedical research but remain underutilize...
Reliable drug safety reference databases are essential for pharmacovigilance, yet existing resourc...
The size of a model has been a strong predictor of its quality, as well as its cost. As such, the ...
Despite decades of advancements in automated ligand screening, large-scale drug discovery remains ...
Ontologies are widely used in databases to standardize data, improving data quality, integration, an...
Causal abstraction techniques such as Interchange Intervention Training (IIT) have been proposed t...