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Derivatization of estrogens enhances specificity and sensitivity of analysis of human plasma and serum by liquid chromatography tandem mass spectrometry.

Estrogens circulate at concentrations less than 20pg/mL in men and postmenopausal women, presenting ...

Predictive modeling of structured electronic health records for adverse drug event detection.

BACKGROUND: The digitization of healthcare data, resulting from the increasingly widespread adoption...

Handling Temporality of Clinical Events for Drug Safety Surveillance.

Using longitudinal data in electronic health records (EHRs) for post-marketing adverse drug event (A...

Pharmacovigilance through the development of text mining and natural language processing techniques.

Text mining for pharmacovigilance: Using machine learning for drug name recognition and drug-drug interaction extraction and classification.

Pharmacovigilance (PV) is defined by the World Health Organization as the science and activities rel...

Extracting Biomedical Event with Dual Decomposition Integrating Word Embeddings.

Extracting biomedical event from literatures has attracted much attention recently. By now, most of ...

Individual prediction of chronic motor outcome in the acute post-stroke stage: Behavioral parameters versus functional imaging.

Several neurobiological factors have been found to correlate with functional recovery after brain le...

On the creation of a clinical gold standard corpus in Spanish: Mining adverse drug reactions.

The advances achieved in Natural Language Processing make it possible to automatically mine informat...

Machine Learning Approach to Optimizing Combined Stimulation and Medication Therapies for Parkinson's Disease.

BACKGROUND: Deep brain stimulation (DBS) of the subthalamic region is an established therapy for adv...

Using swing resistance and assistance to improve gait symmetry in individuals post-stroke.

A major characteristic of hemiplegic gait observed in individuals post-stroke is spatial and tempora...

Toward a complete dataset of drug-drug interaction information from publicly available sources.

Although potential drug-drug interactions (PDDIs) are a significant source of preventable drug-relat...

Multifractal Analysis and Relevance Vector Machine-Based Automatic Seizure Detection in Intracranial EEG.

Automatic seizure detection technology is of great significance for long-term electroencephalogram (...

Pharmacovigilance from social media: mining adverse drug reaction mentions using sequence labeling with word embedding cluster features.

OBJECTIVE: Social media is becoming increasingly popular as a platform for sharing personal health-r...

Assist-as-Needed Robot-Aided Gait Training Improves Walking Function in Individuals Following Stroke.

A novel robot-aided assist-as-needed gait training paradigm has been developed recently. This paradi...

Multistage AI Crop Inspection and Segmentation Framework (MACISF)

Crop quality assessment is one of the most critical components of modern agriculture, which directly...

A high-resolution protein-RNA binding atlas for structure-aware interaction prediction and post-transcriptional regulatory modeling

RNA-binding proteins (RBPs) control post-transcriptional gene expression by regulating RNA processin...

APT: Feedback-Driven Agentic Post-Training for Text-to-Image Generation

Post-training is crucial for improving text-to-image models, yet existing pipelines typically rely o...

Efficient Fréchet Distributional Decoder Alignment for Latent Generative Models

Fréchet Distributional (FD) objectives provide an effective distribution-level signal for post-train...

Rethinking Contrastive Loss in CLIP Post-training: A Complementary Framework with Frozen Text Encoder

CLIP serves as a foundational vision-language model and the de facto vision encoder for downstream V...

Rethinking Contrastive Loss in CLIP Post-training: A Complementary Framework with Frozen Text Encoder

CLIP serves as a foundational vision-language model and the de facto vision encoder for downstream V...

DreamTrue: Action-Faithful Robot World Model with Counterfactual Post-Training

We present DreamTrue, a multi-view, cross-embodiment robot world model for action-faithful and physi...