[HTML][HTML] Natural language processing applied to mental illness detection: a narrative review

T Zhang, AM Schoene, S Ji, S Ananiadou - NPJ digital medicine, 2022 - nature.com
Mental illness is highly prevalent nowadays, constituting a major cause of distress in
people's life with impact on society's health and well-being. Mental illness is a complex multi …

Use of unstructured text in prognostic clinical prediction models: a systematic review

TM Seinen, EA Fridgeirsson, S Ioannou… - Journal of the …, 2022 - academic.oup.com
Objective This systematic review aims to assess how information from unstructured text is
used to develop and validate clinical prognostic prediction models. We summarize the …

[HTML][HTML] Conceptualising fairness: three pillars for medical algorithms and health equity

L Sikstrom, MM Maslej, K Hui, Z Findlay… - BMJ health & care …, 2022 - ncbi.nlm.nih.gov
Objectives Fairness is a core concept meant to grapple with different forms of discrimination
and bias that emerge with advances in Artificial Intelligence (eg, machine learning, ML). Yet …

Enhancing readmission prediction models by integrating insights from home healthcare notes: Retrospective cohort study

S Gan, C Kim, J Chang, DY Lee, RW Park - International Journal of Nursing …, 2024 - Elsevier
Background Hospital readmission is an important indicator of inpatient care quality and a
significant driver of increasing medical costs. Therefore, it is important to explore the effects …

Using large language models to detect outcomes in qualitative studies of adolescent depression

AW **n, DM Nielson, KR Krause… - Journal of the …, 2024 - academic.oup.com
Objective We aim to use large language models (LLMs) to detect mentions of nuanced
psychotherapeutic outcomes and impacts than previously considered in transcripts of …

Psychosis relapse prediction leveraging electronic health records data and natural language processing enrichment methods

DY Lee, C Kim, S Lee, SJ Son, SM Cho, YH Cho… - Frontiers in …, 2022 - frontiersin.org
Background Identifying patients at a high risk of psychosis relapse is crucial for early
interventions. A relevant psychiatric clinical context is often recorded in clinical notes; …

Sentiment classification for employees reviews using regression vector-stochastic gradient descent classifier (RV-SGDC)

B Gaye, D Zhang, A Wulamu - PeerJ Computer Science, 2021 - peerj.com
The satisfaction of employees is very important for any organization to make sufficient
progress in production and to achieve its goals. Organizations try to keep their employees …

The PSYchiatric clinical outcome prediction (PSYCOP) cohort: leveraging the potential of electronic health records in the treatment of mental disorders

L Hansen, KC Enevoldsen, M Bernstorff… - Acta …, 2021 - cambridge.org
Background: The quality of life and lifespan are greatly reduced among individuals with
mental illness. To improve prognosis, the nascent field of precision psychiatry aims to …

Capturing concerns about patient deterioration in narrative documentation in home healthcare

M Hobensack, J Song, S Chae… - AMIA Annual …, 2023 - pmc.ncbi.nlm.nih.gov
Home healthcare (HHC) agencies provide care to more than 3.4 million adults per year.
There is value in studying HHC narrative notes to identify patients at risk for deterioration …

Predicting which patients with cancer will see a psychiatrist or counsellor from their initial oncology consultation document using natural language processing

JJ Nunez, B Leung, C Ho, RT Ng… - Communications Medicine, 2024 - nature.com
Background Patients with cancer often have unmet psychosocial needs. Early detection of
who requires referral to a counsellor or psychiatrist may improve their care. This work used …