Prescriptions

An Exploratory Study on Pseudo-Data Generation in Prescription and Adverse Drug Reaction Extraction.

Prescription information and adverse drug reactions (ADR) are two components of detailed medication instructions that can benefit many aspects of clinical research. Automatic extraction of this information from free-text narratives via Information Extraction (IE) can open it up to downstream uses. IE is commonly tackled by supervised Natural Language Processing (NLP) systems which rely on annotate...

Demand Analysis and Function Design of Health Decision Support System in China.

In order to improve the level of health decision-making, based on health information resources and decision support function types, this study summarized five core functions of health decision support system: information support, monitoring and early warning, analysis and evaluation, trend prediction, comprehensive optimization; And from the perspective of business functions, business processes an...

Effects of In Ovo Vitamin D Injection on Subsequent Growth of Broilers.

This study was conducted to investigate the influence of vitamin D (Vit D) administration on growth of broiler chickens when Vit D was dissolved in s...

Drug knowledge bases and their applications in biomedical informatics research.

Recent advances in biomedical research have generated a large volume of drug-related data. To effectively handle this flood of data, many initiatives ...

Artificial intelligence in drug combination therapy.

Currently, the development of medicines for complex diseases requires the development of combination drug therapies. It is necessary because in many c...

A deep learning model based on sparse auto-encoder for prioritizing cancer-related genes and drug target combinations.

Prioritization of cancer-related genes from gene expression profiles and proteomic data is vital to improve the targeted therapies research. Although ...

Named Entity Recognition and Classification for Medical Prospectuses.

Structuring and processing natural language is a growing challenge in the medical field. Researchers are looking for new ways to extract knowledge to ...

An investigation of single-domain and multidomain medication and adverse drug event relation extraction from electronic health record notes using advanced deep learning models.

OBJECTIVE: We aim to evaluate the effectiveness of advanced deep learning models (eg, capsule network [CapNet], adversarial training [ADV]) for single...

Machine-learning-assisted selection of antibiotic prescription.

Position Based Impedance Control Strategy for a Lower Limb Rehabilitation Robot.

Active rehabilitation training can improve patients' neural engagement and the rehabilitation effects. A position based impedance control strategy is ...

Prediction of patient evolution in terms of Clinical Risk Groups form routinely collected data using machine learning.

Chronicity is a problem that is affecting quality of life and increasing healthcare costs worldwide. Predictive tools can help mitigate these effects ...

Prediction of Personal Experience Tweets of Medication Use via Contextual Word Representations.

Continuous monitoring the safe use of medication is an important task in pharmacovigilance. The first-hand experiences of medication effects come from...

A Social Media Study on the Effects of Psychiatric Medication Use.

Understanding the effects of psychiatric medications during mental health treatment constitutes an active area of inquiry. While clinical trials help ...

Reply to comment on: "Deep learning for pharmacovigilance: recurrent neural network architectures for labeling adverse drug reactions in Twitter posts".

We appreciate the detailed review provided by Magge et al1 of our article, "Deep learning for pharmacovigilance: recurrent neural network architecture...

Comment on: "Deep learning for pharmacovigilance: recurrent neural network architectures for labeling adverse drug reactions in Twitter posts".

Towards an Adaptive Upper Limb Rehabilitation Game with Tangible Robots.

A key feature of a successful game is its ability to provide the player with an adequate level of challenge. However, the objective of difficulty adap...

A novel machine learning-derived decision tree including uPA/PAI-1 for breast cancer care.

Background uPA and PAI-1 are breast cancer biomarkers that evaluate the benefit of chemotherapy (CT) for HER2-negative, estrogen receptor-positive, lo...

Brain activity during reciprocal social interaction investigated using conversational robots as control condition.

We present a novel functional magnetic resonance imaging paradigm for second-person neuroscience. The paradigm compares a human social interaction (hu...

From social brains to social robots: applying neurocognitive insights to human-robot interaction.

Amidst the fourth industrial revolution, social robots are resolutely moving from fiction to reality. With sophisticated artificial agents becoming ev...

In natural interaction with embodied robots, we prefer it when they follow our gaze: a gaze-contingent mobile eyetracking study.

Initiating joint attention by leading someone's gaze is a rewarding experience which facilitates social interaction. Here, we investigate this experie...