Abstract Background Rare Diseases (RDs), which are defined as diseases affecting no more
than 5 out of 10,000 people, are often severe, chronic and life-threatening. A main problem …

To enhance phenotype recognition in clinical notes of genetic diseases, we developed two
models—PhenoBCBERT and PhenoGPT—for expanding the vocabularies of Human …

Background Pectus excavatum (PE) could be part of a genetic disorder, which then has
implications regarding comorbidity, the surgical correction of PE, and reproductive choices …

Purpose Diagnosing monogenic diseases facilitates optimal care, but can involve the
manual evaluation of hundreds of genetic variants per case. Computational tools like Phrank …

Background: Automatic recognition of medical concepts in unstructured text is an important
component of many clinical and research applications, and its accuracy has a large impact …

Motivation Automatic phenotype concept recognition from unstructured text remains a
challenging task in biomedical text mining research. Previous works that address the task …

Abstract Concept recognition tools rely on the availability of textual corpora to assess their
performance and enable the identification of areas for improvement. Typically, corpora are …

Named‐Entity Recognition is commonly used to identify biological entities such as proteins,
genes, and chemical compounds found in scientific articles. The Human Phenotype …

Deep phenotyping followed by integrated computational analysis of genotype and
phenotype is becoming ever more important for many areas of genomic diagnostics and …

Recently, to speed up the differential-diagnosis process based on symptoms and signs
observed from an affected individual in the diagnosis of rare diseases, researchers have …