AIMC Topic: Natural Language Processing

Clear Filters Showing 3341 to 3350 of 3983 articles

Natural Language Processing and Psychosis: On the Need for Comprehensive Psychometric Evaluation.

Schizophrenia bulletin
BACKGROUND AND HYPOTHESIS: Despite decades of "proof of concept" findings supporting the use of Natural Language Processing (NLP) in psychosis research, clinical implementation has been slow. One obstacle reflects the lack of comprehensive psychometr...

Improving the Applicability of AI for Psychiatric Applications through Human-in-the-loop Methodologies.

Schizophrenia bulletin
OBJECTIVES: Machine learning (ML) and natural language processing have great potential to improve efficiency and accuracy in diagnosis, treatment recommendations, predictive interventions, and scarce resource allocation within psychiatry. Researchers...

Survey on natural language processing in medical image analysis.

Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences
Recent advancement in natural language processing (NLP) and medical imaging empowers the wide applicability of deep learning models. These developments have increased not only data understanding, but also knowledge of state-of-the-art architectures a...

GRASCCO - The First Publicly Shareable, Multiply-Alienated German Clinical Text Corpus.

Studies in health technology and informatics
We describe the creation of GRASCCO, a novel German-language corpus composed of some 60 clinical documents with more than.43,000 tokens. GRASCCO is a synthetic corpus resulting from a series of alienation steps to obfuscate privacy-sensitive informat...

Pre-trained models, data augmentation, and ensemble learning for biomedical information extraction and document classification.

Database : the journal of biological databases and curation
Large volumes of publications are being produced in biomedical sciences nowadays with ever-increasing speed. To deal with the large amount of unstructured text data, effective natural language processing (NLP) methods need to be developed for various...

AttentionSiteDTI: an interpretable graph-based model for drug-target interaction prediction using NLP sentence-level relation classification.

Briefings in bioinformatics
In this study, we introduce an interpretable graph-based deep learning prediction model, AttentionSiteDTI, which utilizes protein binding sites along with a self-attention mechanism to address the problem of drug-target interaction prediction. Our pr...

NetSurfP-3.0: accurate and fast prediction of protein structural features by protein language models and deep learning.

Nucleic acids research
Recent advances in machine learning and natural language processing have made it possible to profoundly advance our ability to accurately predict protein structures and their functions. While such improvements are significantly impacting the fields o...

Using Natural Language Processing of Clinical Notes to Predict Outcomes of Opioid Treatment Program.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Potential of natural language processing (NLP) in extracting patient's information from clinical notes of opioid treatment programs (OTP) and leveraging it in development of predictive models has not been fully explored. The goal of this study was to...