AIMC Topic: Natural Language Processing
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User Feedback on the Use of a Natural Language Processing Application to Screen for Suicide Risk in the Emergency Department.
The journal of behavioral health services & research
Feb 3, 2023
Suicide is the 10th leading cause of death in the USA and globally. Despite decades of research, the ability to predict who will die by suicide is still no better than 50%. Traditional screening instruments have helped identify risk factors for suici...
Interaction with Industrial Digital Twin Using Neuro-Symbolic Reasoning.
Sensors (Basel, Switzerland)
Feb 3, 2023
Digital twins have revolutionized manufacturing and maintenance, allowing us to interact with virtual yet realistic representations of the physical world in simulations to identify potential problems or opportunities for improvement. However, traditi...
Evaluation of the portability of computable phenotypes with natural language processing in the eMERGE network.
Scientific reports
Feb 3, 2023
The electronic Medical Records and Genomics (eMERGE) Network assessed the feasibility of deploying portable phenotype rule-based algorithms with natural language processing (NLP) components added to improve performance of existing algorithms using el...
MedLexSp - a medical lexicon for Spanish medical natural language processing.
Journal of biomedical semantics
Feb 2, 2023
BACKGROUND: Medical lexicons enable the natural language processing (NLP) of health texts. Lexicons gather terms and concepts from thesauri and ontologies, and linguistic data for part-of-speech (PoS) tagging, lemmatization or natural language genera...
Predicting the Survival of Patients With Cancer From Their Initial Oncology Consultation Document Using Natural Language Processing.
JAMA network open
Feb 1, 2023
IMPORTANCE: Predicting short- and long-term survival of patients with cancer may improve their care. Prior predictive models either use data with limited availability or predict the outcome of only 1 type of cancer.
Comparison of Chest Radiograph Captions Based on Natural Language Processing vs Completed by Radiologists.
JAMA network open
Feb 1, 2023
IMPORTANCE: Artificial intelligence (AI) can interpret abnormal signs in chest radiography (CXR) and generate captions, but a prospective study is needed to examine its practical value.
Classifying literature mentions of biological pathogens as experimentally studied using natural language processing.
Journal of biomedical semantics
Jan 31, 2023
BACKGROUND: Information pertaining to mechanisms, management and treatment of disease-causing pathogens including viruses and bacteria is readily available from research publications indexed in MEDLINE. However, identifying the literature that specif...
Entity and relation extraction from clinical case reports of COVID-19: a natural language processing approach.
BMC medical informatics and decision making
Jan 26, 2023
BACKGROUND: Extracting relevant information about infectious diseases is an essential task. However, a significant obstacle in supporting public health research is the lack of methods for effectively mining large amounts of health data.
DR.BENCH: Diagnostic Reasoning Benchmark for Clinical Natural Language Processing.
Journal of biomedical informatics
Jan 25, 2023
The meaningful use of electronic health records (EHR) continues to progress in the digital era with clinical decision support systems augmented by artificial intelligence. A priority in improving provider experience is to overcome information overloa...
CARES: A Corpus for classification of Spanish Radiological reports.
Computers in biology and medicine
Jan 23, 2023
This paper presents a new corpus of radiology medical reports written in Spanish and labeled with ICD-10. CARES (Corpus of Anonymised Radiological Evidences in Spanish) is a high-quality corpus manually labeled and reviewed by radiologists that is fr...
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