Assessment of health technology acceptability for remote monitoring of patients with COVID-19: A measurement model for user perceptions of pulse oximeters.

Objective: This study aims to develop a measurement model for health technology acceptability using a theoretical framework and a range of validated instruments to measure user experience, acceptance, usability, health and digital health literacy.

Methods: A cross-sectional evaluation study using a mixed-methods approach was conducted. An online survey was administered to patients who used a pulse oximeter in a virtual hospital setting during COVID-19.

Understanding the factors influencing acceptability of AI in medical imaging domains among healthcare professionals: A scoping review.

Background: Artificial intelligence (AI) technology has the potential to transform medical practice within the medical imaging industry and materially improve productivity and patient outcomes. However, low acceptability of AI as a digital healthcare intervention among medical professionals threatens to undermine user uptake levels, hinder meaningful and optimal value-added engagement, and ultimately prevent these promising benefits from being realised. Understanding the factors underpinning AI acceptability will be vital for medical institutions to pinpoint areas of deficiency and improvement within their AI implementation strategies.

Frequency Domain Channel-Wise Attack to CNN Classifiers in Motor Imagery Brain-Computer Interfaces.

Objective: Convolutional neural network (CNN), a classical structure in deep learning, has been commonly deployed in the motor imagery brain-computer interface (MIBCI). Many methods have been proposed to evaluate the vulnerability of such CNN models, primarily by attacking them using direct temporal perturbations. In this work, we propose a novel attacking approach based on perturbations in the frequency domain instead.

The Plant Defensin Ppdef1 Is a Novel Topical Treatment for Onychomycosis.

Onychomycosis, or fungal nail infection, causes not only pain and discomfort but can also have psychological and social consequences for the patient. Treatment of onychomycosis is complicated by the location of the infection under the nail plate, meaning that antifungal molecules must either penetrate the nail or be applied systemically. Currently, available treatments are limited by their poor nail penetration for topical products or their potential toxicity for systemic products.

Attaining consensus on a core dataset for upper limb lymphoedema using the Delphi method: A foundational step in creating a clinical support system.

Lymphoedema is a condition of localised swelling caused by a compromised lymphatic system. The protein-rich fluid accumulating in the interstitial tissue can create inflammation and irreversible changes to the skin and underlying tissue. An array of methods has been used to assess and report these changes.

Benchmarking the diagnostic test accuracy of certified AI products for screening pulmonary tuberculosis in digital chest radiographs: Preliminary evidence from a rapid review and meta-analysis.

Background And Objective: The global market for AI systems used in lung tuberculosis (TB) detection has expanded significantly in recent years. Verifying their performance across diverse settings is crucial before medical organisations can invest in them and pursue safe, wide-scale deployment. The goal of this research was to synthesise the clinical evidence for the diagnostic accuracy of certified AI products designed for screening TB in chest X-rays (CXRs) compared to a microbiological reference standard.

Patient and Clinician Perceptions of the Pulse Oximeter in a Remote Monitoring Setting for COVID-19: Qualitative Study.

Background: As a response to the COVID-19 pandemic, the Sydney Local Health District in New South Wales, Australia, launched the rpavirtual program, the first full-scale virtual hospital in Australia, to remotely monitor and follow up stable patients with COVID-19. As part of the intervention, a pulse oximeter wearable device was delivered to patients to monitor their oxygen saturation levels, a critical indicator of COVID-19 patient deterioration. Understanding users' perceptions toward the device is fundamental to assessing its usability and acceptability and contributing to the effectiveness of the intervention, but no research to date has explored the user experience of the pulse oximeter for remote monitoring in this setting.

The Impact of an Electronic Medication Management System on Medication Deviations on Admission and Discharge from Hospital.

Medication errors at transition of care remain a concerning issue. In recent times, the use of integrated electronic medication management systems (EMMS) has caused a reduction in medication errors, but its effectiveness in reducing medication deviations at transition of care has not been studied in hospital-wide settings in Australia. The aim of this study is to assess medication deviations, such as omissions and mismatches, pre-EMMS and post-EMMS implementation at transition of care across a hospital.

Phenonizer: A Fine-Grained Phenotypic Named Entity Recognizer for Chinese Clinical Texts.

Biomedical named entity recognition (BioNER) from clinical texts is a fundamental task for clinical data analysis due to the availability of large volume of electronic medical record data, which are mostly in free text format, in real-world clinical settings. Clinical text data incorporates significant phenotypic medical entities (e.g.

Patient and clinician use characteristics and perceptions of pulse oximeter use: A scoping review.

Background And Objectives: The need to monitor patients outside of a formal clinical setting, such as a hospital or ambulatory care facility, has become increasingly important since COVID-19. It introduces significant challenges to ensure accurate and timely measurements, maintain strong patient engagement, and operationalise data for clinical decision-making. Remote Patient Monitoring (RPM) devices like the pulse oximeter help mitigate these difficulties, however, practical approaches to successfully integrate this technology into existing patient-clinician interactions that ensure the delivery of safe and effective care are vital.

Developing a maturity model for cancer multidisciplinary teams.

Background: Multidisciplinary teams (MDTs) are considered the "gold standard" of care for patients with cancer but how well they function and the role they play in decision making varies widely. Although several observational tools have been developed to evaluate MDT performance, they are resource intensive and only assess MDT performance at a static point in time. The aim of this study was to develop a validated maturity model as a self-assessment instrument for MDTs to evaluate their performance and monitor improvement over time.

Implementation of an Electronic Medication Management System in a large tertiary hospital: a case of qualitative inquiry.

Background: Hospitals across Australia are implementing Clinical Information Systems, e.g. Electronic Medication Management Systems (EMMS) at a rapid pace to moderate health services.

A novel method for clinical risk prediction with low-quality data.

In real-world data, predictive models for clinical risks (such as adverse drug reactions, hospital readmission, and chronic disease onset) are constantly struggling with low-quality issues, namely redundant and highly correlated features, extreme category imbalances, and most importantly, a large number of missing values. In most existing work, each patient is represented as a value vector with the fixed-length from some feature space, and missing values are forced to be imputed, which introduces much noise for prediction if the data set is highly incomplete. Besides, other challenges are either remaining unresolved or only partially solved when modeling, but without a systematic approach.

Compliance with Standard Precautions and Its Relationship with Views on Infection Control and Prevention Policy among Healthcare Workers during COVID-19 Pandemic.

: Standard precautions prevent the spread of infections in healthcare settings. Incompliance with infection control guidelines of healthcare workers (HCWs) may increase their risk of exposure to infectious disease, especially under pandemics. The purpose of this study was to assess the level of compliance with the infection prevention and control practices among HCWs in different healthcare settings and its relationship with their views on workplace infection control measures during the COVID-19 pandemic.

Usability evaluation of an integrated electronic medication management system implemented in an oncology setting using the unified theory of the acceptance and use of technology.

Background: Medication management processes in an Oncology setting are complex and difficult to examine in isolation from interrelated processes and contextual factors. This qualitative study aims to evaluate the usability of an Electronic Medication Management System (EMMS) implemented in a specialised oncology unit using the Unified Theory of Acceptance and Use of Technology (UTAUT) framework.

Methods: The study was conducted in a 12-bed outpatient Oncology unit of a major teaching hospital 6 months following implementation of a commercial EMMS.

Medication safety improvements during care transitions in an Australian intensive care unit following implementation of an electronic medication management system.

Background: For patients requiring admission to the Intensive Care Unit (ICU), transfers of care (TOC) during admission to and discharge from the ICU are particularly high-risk periods for medication errors. In the Australian setting, commonly general wards and the ICU do not share an integrated Electronic Medical ecord (EMR) and specifically an Electronic Medication Management System (EMMS) as part of the EMR.

Purpose: To evaluate the effect of a hospital wide integrated EMMS on medication error rates during ICU admission and at TOC.

Clinician Assessment of Upper Limb Lymphedema: An Observational Study.

Clinical management of lymphedema requires assessment, initially for detection, and then for determining treatment response and informing the treatment plan. It is unknown how the components of a lymphedema assessment are used in a clinical environment. Experienced lymphedema therapists were observed assessing patients presenting with new or existing upper body lymphedema.

Improving the Digestibility of Plant Defensins to Meet Regulatory Requirements for Transgene Products in Crop Protection.

Despite the use of chemical fungicides, fungal diseases have a major impact on the yield and quality of plant produce globally and hence there is a need for new approaches for disease control. Several groups have examined the potential use of antifungal plant defensins for plant protection and have produced transgenic plants expressing plant defensins with enhanced resistance to fungal disease. However, before they can be developed commercially, transgenic plants must pass a series of strict regulations to ensure that they are safe for human and animal consumption as well as the environment.

Assessment of Upper Limb Lymphedema: A Qualitative Study Exploring Clinicians' Clinical Reasoning.

A variety of objective and subjective assessments are available for clinical assessment of lymphedema. The aim of this study was to explore the clinical reasoning underpinning the assessment of upper limb lymphedema by experienced lymphedema clinicians. Semistructured, individual, interviews were conducted with lymphedema therapists ( = 14) from a variety of treatment settings.

Machine Learning Clustering for Blood Pressure Variability Applied to Systolic Blood Pressure Intervention Trial (SPRINT) and the Hong Kong Community Cohort.

Visit-to-visit blood pressure variability (BPV) has been shown to be a predictor of cardiovascular disease. We aimed to classify the BPV levels using different machine learning algorithms. Visit-to-visit blood pressure readings were extracted from the SPRINT study in the United States and eHealth cohort in Hong Kong (HK cohort).

The Digitization of the ICU: An Evaluation of Usability and Hospital-Wide Acceptability.

This paper explores the impact of an electronic medication management system (EMMS) on users in an intensive care unit using the Unified Theory and Use of Technology constructs. It also explores the impact of having a consistent EMMS hospital wide, as it is the first Australian hospital to implement the same EMMS hospital wide. The research model was evaluated using survey data from 100 nurses, doctors and pharmacists both within the ICU and externally, to assess the usability and acceptability of the system.

A Deep Learning-Based Approach for Gait Analysis in Huntington Disease.

Huntington Disease (HD) is a genetic neurodegenerative disease which leads to involuntary movements and impaired balance. These changes have been quantified using footstep pressure sensor mats such as Protokinetics' Zeno Walkway. Drawing from distances between recorded footsteps, patients' disease severity have been measured in terms of high level gait characteristics such as gait width and stride length.

Clinical Safety Incident Taxonomy Performance on C4.5 Decision Tree and Random Forest.

The paper applies an artificial intelligence centered method to classify 12 clinical safety incident (CSI) classes. The paper aims to establish a taxonomy that classifies the CSI reports into their correct classes automatically and with high accuracy. The study investigates feasibility of applying the C4.

A suite of kinetically superior AEP ligases can cyclise an intrinsically disordered protein.

Asparaginyl endopeptidases (AEPs) are a class of enzymes commonly associated with proteolysis in the maturation of seed storage proteins. However, a subset of AEPs work preferentially as peptide ligases, coupling release of a leaving group to formation of a new peptide bond. These "ligase-type" AEPs require only short recognition motifs to ligate a range of targets, making them useful tools in peptide and protein engineering for cyclisation of peptides or ligation of separate peptides into larger products.