Publications by authors named "E H Shinohara"
This study demonstrates that adverse events (AEs) extracted using natural language processing (NLP) from clinical texts reflect the known frequencies of AEs associated with anticancer drugs. Using data from 44,502 cancer patients at a single hospital, we identified cases prescribed anticancer drugs (platinum, PLT; taxane, TAX; pyrimidine, PYA) and compared them to non-treatment (NTx) group using propensity score matching. Over 365 days, AEs (peripheral neuropathy, PN; oral mucositis, OM; taste abnormality, TA; appetite loss, AL) were extracted from clinical text using an NLP tool.
View Article and Find Full Text PDFThe aim of this systematic review was to investigate the relationship between fractures of the floor of the orbit (blow outs) and their repercussions on eye movement, based on the available scientific literature. In order to obtain more reliable results, we opted for a methodology that could answer the guiding question of this research. To this end, a systematic review of the literature was carried out, using a rigorous methodological approach.
View Article and Find Full Text PDFAim: To evaluate the effectiveness of an individualized nutritional education program in promoting adequate nutrient intake in pregnant women.
Methods: A stratified randomized controlled trial was conducted. Participants were stratified by factors affecting the primary outcome and randomly assigned to the intervention or control groups.
Article Synopsis
- Senility has emerged as the third leading cause of death in Japan, accounting for 11.4% of total deaths in 2022, showing a concerning rise compared to the decline observed from 1950 to 2000.
- The way senility is recorded on death certificates is often vague, with 93.8% listing only "senility," requiring a more standardized process for accurate documentation.
- Although many prefer to die peacefully without invasive procedures, there is a growing need to recognize and appropriately classify senility as a legitimate cause of death in older adults.
Towards Structuring Clinical Texts: Joint Entity and Relation Extraction from Japanese Case Report Corpus.
Stud Health Technol Inform
January 2024
Important pieces of information related to patient symptoms and diagnosis are often written in free-text form in clinical texts. To utilize these texts, information extraction using natural language processing is required. This study evaluated the performance of named entity recognition (NER) and relation extraction (RE) using machine-learning methods.
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