AIMC Topic: Language

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EGFI: drug-drug interaction extraction and generation with fusion of enriched entity and sentence information.

Briefings in bioinformatics
MOTIVATION: The rapid growth in literature accumulates diverse and yet comprehensive biomedical knowledge hidden to be mined such as drug interactions. However, it is difficult to extract the heterogeneous knowledge to retrieve or even discover the l...

Length of Stay Prediction in Neurosurgery with Russian GPT-3 Language Model Compared to Human Expectations.

Studies in health technology and informatics
Patients, relatives, doctors, and healthcare providers anticipate the evidence-based length of stay (LOS) prediction in neurosurgery. This study aimed to assess the quality of LOS prediction with the GPT3 language model upon the narrative medical rec...

An Evaluation of Pretrained BERT Models for Comparing Semantic Similarity Across Unstructured Clinical Trial Texts.

Studies in health technology and informatics
Processing unstructured clinical texts is often necessary to support certain tasks in biomedicine, such as matching patients to clinical trials. Among other methods, domain-specific language models have been built to utilize free-text information. Th...

BERT-Kcr: prediction of lysine crotonylation sites by a transfer learning method with pre-trained BERT models.

Bioinformatics (Oxford, England)
MOTIVATION: As one of the most important post-translational modifications (PTMs), protein lysine crotonylation (Kcr) has attracted wide attention, which involves in important physiological activities, such as cell differentiation and metabolism. Howe...

Entity recognition of Chinese medical text based on multi-head self-attention combined with BILSTM-CRF.

Mathematical biosciences and engineering : MBE
Named entities are the main carriers of relevant medical knowledge in Electronic Medical Records (EMR). Clinical electronic medical records lead to problems such as word segmentation ambiguity and polysemy due to the specificity of Chinese language s...

[What worries people with multiple sclerosis in Russia? Semantic analysis of patient messages using artificial intelligence tools].

Zhurnal nevrologii i psikhiatrii imeni S.S. Korsakova
OBJECTIVE: To study the needs of patients suffering from multiple sclerosis (MS) in Russia.

BioBERT and Similar Approaches for Relation Extraction.

Methods in molecular biology (Clifton, N.J.)
In biomedicine, facts about relations between entities (disease, gene, drug, etc.) are hidden in the large trove of 30 million scientific publications. The curated information is proven to play an important role in various applications such as drug r...

Identifying Mild Cognitive Impairment by Using Human-Robot Interactions.

Journal of Alzheimer's disease : JAD
BACKGROUND: Mild cognitive impairment (MCI), which is common in older adults, is a risk factor for dementia. Rapidly growing health care demand associated with global population aging has spurred the development of new digital tools for the assessmen...

De Novo Molecular Design with Chemical Language Models.

Methods in molecular biology (Clifton, N.J.)
Artificial intelligence (AI) offers new possibilities for hit and lead finding in medicinal chemistry. Several instances of AI have been used for prospective de novo drug design. Among these, chemical language models have been shown to perform well i...

Extraction of Temporal Structures for Clinical Events in Unlabeled Free-Text Electronic Health Records in Russian.

Studies in health technology and informatics
The important information about a patient is often stored in a free-form text to describe the events in the patient's medical history. In this work, we propose and evaluate a hybrid approach based on rules and syntactical analysis to normalise tempor...