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] Applications of the natural language processing tool ChatGPT in clinical practice: comparative study and augmented systematic review

N Schopow, G Osterhoff, D Baur - JMIR Medical Informatics, 2023 - medinform.jmir.org
Background This research integrates a comparative analysis of the performance of human
researchers and OpenAI's ChatGPT in systematic review tasks and describes an …

Machine learning-based early prediction of sepsis using electronic health records: a systematic review

KR Islam, J Prithula, J Kumar, TL Tan… - Journal of clinical …, 2023 - mdpi.com
Background: Sepsis, a life-threatening infection-induced inflammatory condition, has
significant global health impacts. Timely detection is crucial for improving patient outcomes …

Data heterogeneity in federated learning with Electronic Health Records: Case studies of risk prediction for acute kidney injury and sepsis diseases in critical care

S Rajendran, Z Xu, W Pan, A Ghosh… - PLOS Digital Health, 2023 - journals.plos.org
With the wider availability of healthcare data such as Electronic Health Records (EHR), more
and more data-driven based approaches have been proposed to improve the quality-of-care …

Bending the patient safety curve: how much can AI help?

DC Classen, C Longhurst, EJ Thomas - NPJ Digital Medicine, 2023 - nature.com
This paper reviews the current state of patient safety and the application of artificial
intelligence (AI) techniques to patient safety. This paper defines patient safety broadly, not …

Unleashing the power of explainable AI: sepsis sentinel's clinical assistant for early sepsis identification

S Chakraborty, K Kumar, K Tadepalli, BR Pailla… - Multimedia Tools and …, 2024 - Springer
Sepsis is a severe and potentially life-threatening condition that occurs when the body's
immune response becomes excessively intense in reaction to an infection. If not promptly …

Systematic reviews of machine learning in healthcare: a literature review

K Kolasa, B Admassu… - Expert Review of …, 2024 - Taylor & Francis
Introduction The increasing availability of data and computing power has made machine
learning (ML) a viable approach to faster, more efficient healthcare delivery. Methods A …

Screening tools for sepsis identification in paramedicine and other emergency contexts: a rapid systematic review

M De Silva, W Chadwick, N Naidoo - Scandinavian Journal of Trauma …, 2023 - Springer
Background Sepsis is a life-threatening condition that contributes significantly to protracted
hospitalisations globally. The unique positioning of paramedics and other emergency care …

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 …

[HTML][HTML] A customised down-sampling machine learning approach for sepsis prediction

Q Wu, F Ye, Q Gu, F Shao, X Long, Z Zhan… - International Journal of …, 2024 - Elsevier
Objective Sepsis is a life-threatening condition in the ICU and requires treatment in time.
Despite the accuracy of existing sepsis prediction models, insufficient focus on reducing …