AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Biomedical Research

Showing 331 to 340 of 545 articles

Clear Filters

Chemical-induced disease relation extraction with dependency information and prior knowledge.

Journal of biomedical informatics
Chemical-disease relation (CDR) extraction is significantly important to various areas of biomedical research and health care. Nowadays, many large-scale biomedical knowledge bases (KBs) containing triples about entity pairs and their relations have ...

Future Direction for Using Artificial Intelligence to Predict and Manage Hypertension.

Current hypertension reports
PURPOSE OF REVIEW: Evidence that artificial intelligence (AI) is useful for predicting risk factors for hypertension and its management is emerging. However, we are far from harnessing the innovative AI tools to predict these risk factors for hyperte...

Identification of research hypotheses and new knowledge from scientific literature.

BMC medical informatics and decision making
BACKGROUND: Text mining (TM) methods have been used extensively to extract relations and events from the literature. In addition, TM techniques have been used to extract various types or dimensions of interpretative information, known as Meta-Knowled...

Exploiting semantic patterns over biomedical knowledge graphs for predicting treatment and causative relations.

Journal of biomedical informatics
BACKGROUND: Identifying new potential treatment options for medical conditions that cause human disease burden is a central task of biomedical research. Since all candidate drugs cannot be tested with animal and clinical trials, in vitro approaches a...

Leveraging Wikipedia knowledge to classify multilingual biomedical documents.

Artificial intelligence in medicine
This article presents a classifier that leverages Wikipedia knowledge to represent documents as vectors of concepts weights, and analyses its suitability for classifying biomedical documents written in any language when it is trained only with Englis...

Automated screening of research studies for systematic reviews using study characteristics.

Systematic reviews
BACKGROUND: Screening candidate studies for inclusion in a systematic review is time-consuming when conducted manually. Automation tools could reduce the human effort devoted to screening. Existing methods use supervised machine learning which train ...

The inhibitory effect of functional lesions on eloquent brain areas: from research bench to operating bed.

The International journal of neuroscience
Functioning, but injured cerebral connections are hypothesized to inhibit cortical plasticity. Study of neural networks can validate this hypothesis, and provide further practical clues for clinical and surgical options to restore function in eloque...

ProvCaRe Semantic Provenance Knowledgebase: Evaluating Scientific Reproducibility of Research Studies.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Scientific reproducibility is critical for biomedical research as it enables us to advance science by building on previous results, helps ensure the success of increasingly expensive drug trials, and allows funding agencies to make informed decisions...

A bibliometric analysis of natural language processing in medical research.

BMC medical informatics and decision making
BACKGROUND: Natural language processing (NLP) has become an increasingly significant role in advancing medicine. Rich research achievements of NLP methods and applications for medical information processing are available. It is of great significance ...

Training replicable predictors in multiple studies.

Proceedings of the National Academy of Sciences of the United States of America
This article considers replicability of the performance of predictors across studies. We suggest a general approach to investigating this issue, based on ensembles of prediction models trained on different studies. We quantify how the common practice...