Journal of Medical Systems

In medical and biomedical education, traditional teaching methods often struggle to engage students and promote critical thinking. The use of AI language models has the potential to transform teaching and learning practices by offering an innovative, active learning approach that promotes intellectual curiosity and deeper understanding. To effectively integrate AI language models into biomedical education, it is essential for educators to understand the benefits and limitations of these tools and how they can be employed to achieve high-level learning outcomes...

The Stanford Biodesign needs-centric framework can guide healthcare innovators to successfully adopt the 'Identify, Invent and Implement' framework and develop new healthcare innovations products to address patients' needs. This scoping review explored the application of the Stanford Biodesign framework for healthcare innovation training and the development of novel healthcare innovative products. Seven electronic databases were searched from their respective inception dates till April 2023: PubMed, Embase, CINAHL, PsycINFO, Web of Science, Scopus, ProQuest Dissertations, and Theses Global...

Polypharmacy remains an important challenge for patients with extensive medical complexity. Given the primary care shortage and the increasing aging population, effective polypharmacy management is crucial to manage the increasing burden of care. The capacity of large language model (LLM)-based artificial intelligence to aid in polypharmacy management has yet to be evaluated. Here, we evaluate ChatGPT's performance in polypharmacy management via its deprescribing decisions in standardized clinical vignettes...

The Electronic Personal Health Record (EPHR) provides an innovative service for citizens and professionals to manage health data, promoting patient-centred care. It enhances communication between patients and physicians and improves accessibility to documents for remote medical information management. The study aims to assess the prevalence of awareness and acceptance of the EPHR in northern Italy and define determinants and barriers to its implementation. In 2022, a region-wide cross-sectional study was carried out through a paper-based and online survey shared among adult citizens...

Wrong dose calculation medication errors are widespread in pediatric patients mainly due to weight-based dosing. PediPain app is a clinical decision support tool that provides weight- and age- based dosages for various analgesics. We hypothesized that the use of a clinical decision support tool, the PediPain app versus pocket calculators for calculating pain medication dosages in children reduces the incidence of wrong dosage calculations and shortens the time taken for calculations. The study was a randomised controlled trial comparing the PediPain app vs...

Clinicians and patients seeking electronic health applications face challenges in selecting effective solutions due to a high market failure rate. Conversational agent applications ("chatbots") show promise in increasing healthcare user engagement by creating bonds between the applications and users. It is unclear if chatbots improve patient adherence or if past trends to include chatbots in electronic health applications were due to technology hype dynamics and competitive pressure to innovate. We conducted a systematic literature review using Preferred Reporting Items for Systematic reviews and Meta-Analyses methodology on health chatbot randomized control trials...

Transvaginal oocyte retrieval is an outpatient procedure performed under local anaesthesia. Hypno-analgesia could be effective in managing comfort during this procedure. This study aimed to assess the effectiveness of a virtual reality headset as an adjunct to local anaesthesia in managing nociception during oocyte retrieval. This was a prospective, randomized single-centre study including patients undergoing oocyte retrieval under local anaesthesia. Patients were randomly assigned to the intervention group (virtual reality headset + local anaesthesia) or the control group (local anaesthesia)...

The aim of the study is to evaluate and compare the quality and readability of responses generated by five different artificial intelligence (AI) chatbots-ChatGPT, Bard, Bing, Ernie, and Copilot-to the top searched queries of erectile dysfunction (ED). Google Trends was used to identify ED-related relevant phrases. Each AI chatbot received a specific sequence of 25 frequently searched terms as input. Responses were evaluated using DISCERN, Ensuring Quality Information for Patients (EQIP), and Flesch-Kincaid Grade Level (FKGL) and Reading Ease (FKRE) metrics...

Computed tomography perfusion (CTP) is a dynamic 4-dimensional imaging technique (3-dimensional volumes captured over approximately 1 min) in which cerebral blood flow is quantified by tracking the passage of a bolus of intravenous contrast with serial imaging of the brain. To diagnose and assess acute ischemic stroke, the standard method relies on summarizing acquired CTPs over the time axis to create maps that show different hemodynamic parameters, such as the timing of the bolus arrival and passage (Tmax and MTT), cerebral blood flow (CBF), and cerebral blood volume (CBV)...

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This retrospective study assessed the effectiveness and impact of implementing a Modified Early Warning System (MEWS) and Rapid Response Team (RRT) for inpatients admitted to the general ward (GW) of a medical center. This study included all inpatients who stayed in GWs from Jan. 2017 to Feb. 2022. We divided inpatients into GWnon-MEWS and GWMEWS groups according to MEWS and RRT implementation in Aug. 2019. The primary outcome, unexpected deterioration, was defined by unplanned admission to intensive care units...

Anesthesiologists have a significant responsibility to provide care at all hours of the day, including nights, weekends, and holidays. This call burden carries a significant lifestyle constraint that can impact relationships, affect provider wellbeing, and has been associated with provider burnout. This quality improvement study analyzes the effects of a dynamic call marketplace, which allows anesthesiologists to specify how much call they would like to take across a spectrum of hypothetical compensation levels, from very low to very high...

In today's data-driven world, the exponential growth of digital information poses significant challenges in data management. In recent years, the adoption of cloud-based Electronic Health Records (EHR) sharing schemes has yielded numerous advantages like improved accessibility, availability, and enhanced interoperability. However, the centralized nature of cloud storage presents challenges in terms of information storage, privacy protection, and security. Despite several approaches that have been presented to ensure secure deduplication of similar EHRs, the validation of data integrity without a third-party auditor (TPA) remains a persistent task...

In healthcare professions, soft skills contribute to critical thinking, decision-making, and patient-centered care. While important to the delivery of high-quality medical care, soft skills are often underemphasized during healthcare training in low-and-middle-income countries. Despite South Asia's large population, the efficacy and viability of a digital soft skills curriculum for South Asian healthcare practitioners has not been studied to date. We hypothesized that a web-based, multilingual, soft skills course could aid the understanding and application of soft skills to improve healthcare practitioner knowledge, confidence, attitudes, and intent-to-change clinical practice...

Intraoperative cardiopulmonary variables are well-known predictors of postoperative pulmonary complications (PPC), traditionally quantified by median values over the duration of surgery. However, it is unknown whether cardiopulmonary instability, or wider intra-operative variability of the same metrics, is distinctly associated with PPC risk and severity. We leveraged a retrospective cohort of adults (n = 1202) undergoing major non-cardiothoracic surgery. We used multivariable logistic regression to evaluate the association of two outcomes (1)moderate-or-severe PPC and (2)any PPC with two sets of exposure variables- (a)variability of cardiopulmonary metrics (inter-quartile range, IQR) and (b)median intraoperative cardiopulmonary metrics...

Although magnetic resonance imaging (MRI) data of patients with multiple myeloma (MM) are used to predict prognosis, few reports have applied artificial intelligence (AI) techniques for this purpose. We aimed to analyze whole-body diffusion-weighted MRI data using three-dimensional (3D) convolutional neural networks (CNNs) and Gradient-weighted Class Activation Mapping (Grad-CAM), an explainable AI, to predict prognosis and explore the factors involved in prediction. We retrospectively analyzed the MRI data of a total of 142 patients with MM obtained from two medical centers...

BACKGROUND: The Virtual Reality Headset (VRH) is a device aiming at improving patient's comfort by reducing pain and anxiety during medical interventions. Its interest during cardiac implantable electronic devices (CIED) implant procedures has not been studied. METHODS: We randomized consecutive patients admitted for pacemaker or Implantable Cardioverter Defibrillator (ICD) at our center to either standard analgesia care (STD-Group), or to VRH (VRH-Group). Patients in the STD-Group received intra-venous paracetamol (1 g) 60 min before the procedure, and local anesthesia was performed with lidocaine...

Schizophrenia is a serious chronic mental disorder that significantly affects daily life. Electroencephalography (EEG), a method used to measure mental activities in the brain, is among the techniques employed in the diagnosis of schizophrenia. The symptoms of the disease typically begin in childhood and become more pronounced as one grows older. However, it can be managed with specific treatments. Computer-aided methods can be used to achieve an early diagnosis of this illness. In this study, various machine learning algorithms and the emerging technology of quantum-based machine learning algorithm were used to detect schizophrenia using EEG signals...

INTRODUCTION: ChatGPT, a recently released chatbot from OpenAI, has found applications in various aspects of life, including academic research. This study investigated the knowledge, perceptions, and attitudes of researchers towards using ChatGPT and other chatbots in academic research. METHODS: A pre-designed, self-administered survey using Google Forms was employed to conduct the study. The questionnaire assessed participants' knowledge of ChatGPT and other chatbots, their awareness of current chatbot and artificial intelligence (AI) applications, and their attitudes towards ChatGPT and its potential research uses...

Clinical abbreviation disambiguation is a crucial task in the biomedical domain, as the accurate identification of the intended meanings or expansions of abbreviations in clinical texts is vital for medical information retrieval and analysis. Existing approaches have shown promising results, but challenges such as limited instances and ambiguous interpretations persist. In this paper, we propose an approach to address these challenges and enhance the performance of clinical abbreviation disambiguation. Our objective is to leverage the power of Large Language Models (LLMs) and employ a Generative Model (GM) to augment the dataset with contextually relevant instances, enabling more accurate disambiguation across diverse clinical contexts...