[HTML][HTML] A systematic review of clinical decision support systems for antimicrobial management: are we failing to investigate these interventions appropriately?
Objectives Clinical decision support systems (CDSS) for antimicrobial management can
support clinicians to optimize antimicrobial therapy. We reviewed all original literature …
support clinicians to optimize antimicrobial therapy. We reviewed all original literature …
Big data and artificial intelligence in the banking industry
Big data and artificial intelligence (AI) assist businesses with decision-making. They help
companies create new products and processes or improve existing ones. As the amount of …
companies create new products and processes or improve existing ones. As the amount of …
[HTML][HTML] Supervised learning for infection risk inference using pathology data
Abstract Background Antimicrobial Resistance is threatening our ability to treat common
infectious diseases and overuse of antimicrobials to treat human infections in hospitals is …
infectious diseases and overuse of antimicrobials to treat human infections in hospitals is …
Supervised machine learning for the prediction of infection on admission to hospital: a prospective observational cohort study
Background Infection diagnosis can be challenging, relying on clinical judgement and non-
specific markers of infection. We evaluated a supervised machine learning (SML) algorithm …
specific markers of infection. We evaluated a supervised machine learning (SML) algorithm …
[HTML][HTML] Machine learning and synthetic outcome estimation for individualised antimicrobial cessation
The decision on when it is appropriate to stop antimicrobial treatment in an individual patient
is complex and under-researched. Ceasing too early can drive treatment failure, while …
is complex and under-researched. Ceasing too early can drive treatment failure, while …
Usage of model driven environment for the classification of ECG features: A systematic review
Electrocardiography (ECG) constitutes a perfect and primary diagnostic tool for measuring
the different morbidity conditions of the heart in the context of different heart diseases and …
the different morbidity conditions of the heart in the context of different heart diseases and …
[HTML][HTML] A risk-based clinical decision support system for patient-specific antimicrobial therapy (iBiogram): design and retrospective analysis
L Müller, A Srinivasan, SR Abeles, A Rajagopal… - Journal of Medical …, 2021 - jmir.org
Background There is a pressing need for digital tools that can leverage big data to help
clinicians select effective antibiotic treatments in the absence of timely susceptibility data …
clinicians select effective antibiotic treatments in the absence of timely susceptibility data …
Supervised machine learning to support the diagnosis of bacterial infection in the context of COVID-19
Background Bacterial infection has been challenging to diagnose in patients with COVID-19.
We developed and evaluated supervised machine learning algorithms to support the …
We developed and evaluated supervised machine learning algorithms to support the …
[HTML][HTML] Development of a patient-centred intervention to improve knowledge and understanding of antibiotic therapy in secondary care
Background We developed a personalised antimicrobial information module co-designed
with patients. This study aimed to evaluate the potential impact of this patient-centred …
with patients. This study aimed to evaluate the potential impact of this patient-centred …
[HTML][HTML] Resistance trend estimation using regression analysis to enhance antimicrobial surveillance: a multi-centre study in London 2009–2016
B Hernandez, P Herrero-Viñas, TM Rawson… - Antibiotics, 2021 - mdpi.com
In the last years, there has been an increase of antimicrobial resistance rates around the
world with the misuse and overuse of antimicrobials as one of the main leading drivers. In …
world with the misuse and overuse of antimicrobials as one of the main leading drivers. In …