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tit all "Natural language processing."
im Bestand: Gesamter Bestand
271 - 280 von 401
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271
Identifying COVID-19 cases and extracting patient reported symptoms from Reddit using natural language processing
Enthalten in Scientific reports Bd. 13, 22.8.2023, Nr. 1, date:12.2023: 1-13
272
Identifying people with potentially undiagnosed dementia with Lewy bodies using natural language processing
Enthalten in npj aging Bd. 11, 18.7.2025, Nr. 1, date:12.2025: 1-7
273
Identifying Suicide Ideation and Suicidal Attempts in a Psychiatric Clinical Research Database using Natural Language Processing
Enthalten in Scientific reports Bd. 8, 9.5.2018, Nr. 1, date:12.2018: 1-10
274
Impact of EU non-financial reporting regulation on Spanish companies’ environmental disclosure: a cutting-edge natural language processing approach
Enthalten in Environmental sciences Europe Bd. 37, 21.2.2025, Nr. 1, date:12.2025: 1-33
275
Improving ascertainment of suicidal ideation and suicide attempt with natural language processing
Enthalten in Scientific reports Bd. 12, 7.9.2022, Nr. 1, date:12.2022: 1-11
276
Improving early diagnosis of rare diseases using Natural Language Processing in unstructured medical records: an illustration from Dravet syndrome
Enthalten in Orphanet journal of rare diseases Bd. 16, 13.7.2021, Nr. 1, date:12.2021: 1-12
277
Improving triage performance in emergency departments using machine learning and natural language processing: a systematic review
Enthalten in BMC emergency medicine Bd. 24, 18.11.2024, Nr. 1, date:12.2024: 1-29
278
In patients’ words: natural language processing of reports from patients experiencing orofacial pain and dysfunction
Enthalten in The journal of headache and pain Bd. 26, 30.7.2025, Nr. 1, date:12.2025: 1-13
279
Informing the development of an outcome set and banks of items to measure mobility among individuals with acquired brain injury using natural language processing
Enthalten in BMC neurology Bd. 22, 9.12.2022, Nr. 1, date:12.2022: 1-15
280
Integrating structured and unstructured data for predicting emergency severity: an association and predictive study using transformer-based natural language processing models
Enthalten in BMC medical informatics and decision making Bd. 24, 5.12.2024, Nr. 1, date:12.2024: 1-13
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