Journal of the American Medical Informatics Association This is an RSS file. You can use it to subscribe to this data in your favourite RSS reader or to display this data on your own website or blog.

Deep-learning-based automated terminology mapping in OMOP-CDM
ConclusionIncorporating the semantics of code descriptions more significantly increases matching accuracy compared to traditional text co-occurrence-based approaches. The negative training sample collection methodology is also an important component of the proposed trainable system that can be adopted in both present and future related systems. (Source: Journal of the American Medical Informatics Association)
Source: Journal of the American Medical Informatics Association - May 13, 2021 Category: Information Technology Source Type: research

Real-Time Electronic Health Record Mortality Prediction During the COVID-19 Pandemic: A Prospective Cohort Study
ConclusionWe developed and validated an accurate in-hospital mortality prediction score in a live EHR for automatic and continuous calculation using a novel model that improved upon SOFA. (Source: Journal of the American Medical Informatics Association)
Source: Journal of the American Medical Informatics Association - May 10, 2021 Category: Information Technology Source Type: research

Stroke risk prediction using machine learning: a prospective cohort study of 0.5 million Chinese adults
ConclusionAmong several approaches, an ensemble model combining both GBT and Cox models achieved the best performance for identifying individuals at high risk of stroke in a contemporary study of Chinese adults. The results highlight the potential value of expanding the use of ML in clinical practice. (Source: Journal of the American Medical Informatics Association)
Source: Journal of the American Medical Informatics Association - May 9, 2021 Category: Information Technology Source Type: research

Pharmacists ’ perceptions of a machine learning model for the identification of atypical medication orders
ConclusionsBased on the AUPR, this model showed better performance for the identification of atypical pharmacological profiles than for medication orders. Pharmacists considered the model a useful screening tool. Improving these predictions should be prioritized in future research to maximize clinical impact. (Source: Journal of the American Medical Informatics Association)
Source: Journal of the American Medical Informatics Association - May 6, 2021 Category: Information Technology Source Type: research

A neuro-symbolic method for understanding free-text medical evidence
ConclusionsMD-informed attention empowers neural reading comprehension models with interpretability and generalizability via reusable domain knowledge. Its compositionality can benefit any transformer-based architecture for machine reading comprehension of free-text medical evidence. (Source: Journal of the American Medical Informatics Association)
Source: Journal of the American Medical Informatics Association - May 6, 2021 Category: Information Technology Source Type: research

Corrigendum: Conflicting information from the Food and Drug Administration: Missed opportunity to lead standards for safe and effective medical artificial intelligence solutions
Journal of the American Medical Informatics Association, 2021, doi: 10.1093/jamia/ocab035 (Source: Journal of the American Medical Informatics Association)
Source: Journal of the American Medical Informatics Association - May 5, 2021 Category: Information Technology Source Type: research

Corrigendum to: Practice and market factors associated with provider volume of health information exchange
Journal of the American Medical Informatics Association, doi: 10.1093/jamia/ocab024 (Source: Journal of the American Medical Informatics Association)
Source: Journal of the American Medical Informatics Association - May 5, 2021 Category: Information Technology Source Type: research

Finding commonalities in rare diseases through the undiagnosed diseases network
ConclusionThis study shows that despite the scarcity and heterogeneity of patients, we can still find commonalities that can potentially be harnessed to uncover new insights and targets for therapy. (Source: Journal of the American Medical Informatics Association)
Source: Journal of the American Medical Informatics Association - May 3, 2021 Category: Information Technology Source Type: research

Identifying risk of opioid use disorder for patients taking opioid medications with deep learning
ConclusionsLSTM –based sequential deep learning models can accurately predict OUD using a patient’s history of electronic health records, with minimal prior domain knowledge. This tool has the potential to improve clinical decision support for early intervention and prevention to combat the opioid epidemic. (Source: Journal of the American Medical Informatics Association)
Source: Journal of the American Medical Informatics Association - April 30, 2021 Category: Information Technology Source Type: research

Measuring time clinicians spend using EHRs in the inpatient setting: a national, mixed-methods study
ConclusionAlthough half of US hospitals use measures of time spent in the EHR derived from EHR generated data, work remains to make such measures and analyses more broadly available to all hospitals and to increase its utility for national burden measurement. (Source: Journal of the American Medical Informatics Association)
Source: Journal of the American Medical Informatics Association - April 26, 2021 Category: Information Technology Source Type: research

Barriers to using clinical decision support in ambulatory care: Do clinics in health systems fare better?
ConclusionsCDS barriers related to resources and user acceptance remained substantial. Health systems, while being effective in promoting CDS tools, may need to provide further assistance to their affiliated ambulatory clinics to overcome barriers, especially the requirement to redesign workflow. Rural clinics may need more resources for training. (Source: Journal of the American Medical Informatics Association)
Source: Journal of the American Medical Informatics Association - April 25, 2021 Category: Information Technology Source Type: research

Enhancing trust in AI through industry self-governance
AbstractArtificial intelligence (AI) is critical to harnessing value from exponentially growing health and healthcare data. Expectations are high for AI solutions to effectively address current health challenges. However, there have been prior periods of enthusiasm for AI followed by periods of disillusionment, reduced investments, and progress, known as “AI Winters.” We are now at risk of another AI Winter in health/healthcare due to increasing publicity of AI solutions that are not representing touted breakthroughs, and thereby decreasing trust of users in AI. In this article, we first highlight recently published li...
Source: Journal of the American Medical Informatics Association - April 25, 2021 Category: Information Technology Source Type: research

Enabling adoption and use of new health information technology during implementation: Roles and strategies for internal and external support personnel
ConclusionsThese findings suggest that institutional investment in technology training and explicit programs to foster skills in mediation, including roles for professionals with career development opportunities, prior to implementation can be beneficial in easing the pain of system transition. (Source: Journal of the American Medical Informatics Association)
Source: Journal of the American Medical Informatics Association - April 24, 2021 Category: Information Technology Source Type: research

Using nursing notes to improve clinical outcome prediction in intensive care patients: A retrospective cohort study
ConclusionsOur findings demonstrate that statistical models derived from text analysis in the first 48 hours of ICU admission can predict patient outcomes. Physicians ’ and nurses’ notes are both uniquely important in mortality prediction and combining these notes can produce a better predictive model. (Source: Journal of the American Medical Informatics Association)
Source: Journal of the American Medical Informatics Association - April 21, 2021 Category: Information Technology Source Type: research

RTEX: A novel framework for ranking, tagging, and explanatory diagnostic captioning of radiography exams
ConclusionsThis is the first framework that successfully combines 3 tasks: ranking, tagging, and diagnostic captioning with focus on radiography exams that contain abnormalities. (Source: Journal of the American Medical Informatics Association)
Source: Journal of the American Medical Informatics Association - April 21, 2021 Category: Information Technology Source Type: research