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Public Health Public Health

Acceptability and Effectiveness of COVID-19 Contact Tracing Applications: A Case Study in Saudi Arabia of the Tawakkalna Application.

In Cureus

Background Contact tracing applications were introduced during the COVID-19 pandemic to mitigate the spread of the infection in several countries. In Saudi Arabia, the Tawakkalna application was developed. The Tawakkalna application is a mobile health solution aimed to track infection cases, save lives, and reduce the burden on health facilities. This study aims to explore the public's attitude to and acceptance levels of the Tawakkalna application and to evaluate its effectiveness regarding privacy and security. The main objective of this study is to investigate the user acceptability of contact tracing applications and explore the safety and privacy effectiveness of the COVID-19 contact tracing application, the Tawakkalna application. In addition, the study analyzes factors associated with acceptance levels and compares the results obtained to similar studies in other countries using similar applications. Methodology This study used a valid and reliable online survey that was used in similar studies conducted in other countries to assess the acceptability of the application. The survey was conducted from September to November 2021, and the final dataset included 205 participants. To investigate the privacy and security performance of the Tawakkalna application, we followed the investigation method used by similar research that investigated 28 contact tracing applications across Europe. Results Out of the 205 participants, 84.87% were in favor of the opt-in voluntary installation of the Tawakkalna application, and 49.75% of the participants were in favor of the opt-out automatic installation. Individuals' trust in the government had a huge impact on acceptance, with 60.98% of the participants supporting the application because they believed that the Tawakkalna application would help them stay healthy during the COVID-19 pandemic. Overall, 49% of the participants supporting the application also agreed to the de-identification of their collected data and providing it for research. The Tawakkalna application ranked at the top compared to other contact tracing applications regarding privacy and security. Conclusions The Tawakkalna application developed by the Saudi Data and Artificial Intelligence Authority was a response to the COVID-19 pandemic, which is considered the biggest public health crisis in recent times. The Saudi Arabian government gained the population's acceptance through effective endorsement and the spread of educational content through media channels. By complying with privacy policies, the Tawakkalna application is an effective tool to combat public health infectious diseases.

Dawood Safia, AlKadi Khulud

2023-Feb

acceptability, contact tracing, covid-19, mhealth, permission, privacy, privilege, security, tawakkalna

oncology Oncology

ExBEHRT: Extended Transformer for Electronic Health Records to Predict Disease Subtypes & Progressions

ArXiv Preprint

In this study, we introduce ExBEHRT, an extended version of BEHRT (BERT applied to electronic health records), and apply different algorithms to interpret its results. While BEHRT considers only diagnoses and patient age, we extend the feature space to several multimodal records, namely demographics, clinical characteristics, vital signs, smoking status, diagnoses, procedures, medications, and laboratory tests, by applying a novel method to unify the frequencies and temporal dimensions of the different features. We show that additional features significantly improve model performance for various downstream tasks in different diseases. To ensure robustness, we interpret model predictions using an adaptation of expected gradients, which has not been previously applied to transformers with EHR data and provides more granular interpretations than previous approaches such as feature and token importances. Furthermore, by clustering the model representations of oncology patients, we show that the model has an implicit understanding of the disease and is able to classify patients with the same cancer type into different risk groups. Given the additional features and interpretability, ExBEHRT can help make informed decisions about disease trajectories, diagnoses, and risk factors of various diseases.

Maurice Rupp, Oriane Peter, Thirupathi Pattipaka

2023-03-22

Surgery Surgery

Early Triage of Critically Ill Adult Patients With Mushroom Poisoning: Machine Learning Approach.

In JMIR formative research

BACKGROUND : Early triage of patients with mushroom poisoning is essential for administering precise treatment and reducing mortality. To our knowledge, there has been no established method to triage patients with mushroom poisoning based on clinical data.

OBJECTIVE : The purpose of this work was to construct a triage system to identify patients with mushroom poisoning based on clinical indicators using several machine learning approaches and to assess the prediction accuracy of these strategies.

METHODS : In all, 567 patients were collected from 5 primary care hospitals and facilities in Enshi, Hubei Province, China, and divided into 2 groups; 322 patients from 2 hospitals were used as the training cohort, and 245 patients from 3 hospitals were used as the test cohort. Four machine learning algorithms were used to construct the triage model for patients with mushroom poisoning. Performance was assessed using the area under the receiver operating characteristic curve (AUC), decision curve, sensitivity, specificity, and other representative statistics. Feature contributions were evaluated using Shapley additive explanations.

RESULTS : Among several machine learning algorithms, extreme gradient boosting (XGBoost) showed the best discriminative ability in 5-fold cross-validation (AUC=0.83, 95% CI 0.77-0.90) and the test set (AUC=0.90, 95% CI 0.83-0.96). In the test set, the XGBoost model had a sensitivity of 0.93 (95% CI 0.81-0.99) and a specificity of 0.79 (95% CI 0.73-0.85), whereas the physicians' assessment had a sensitivity of 0.86 (95% CI 0.72-0.95) and a specificity of 0.66 (95% CI 0.59-0.73).

CONCLUSIONS : The 14-factor XGBoost model for the early triage of mushroom poisoning can rapidly and accurately identify critically ill patients and will possibly serve as an important basis for the selection of treatment options and referral of patients, potentially reducing patient mortality and improving clinical outcomes.

Liu Yuxuan, Lyu Xiaoguang, Yang Bo, Fang Zhixiang, Hu Dejun, Shi Lei, Wu Bisheng, Tian Yong, Zhang Enli, Yang YuanChao

2023-Mar-21

XGBoost, extreme gradient boosting, machine learning, model, mushroom poisoning, triage

Internal Medicine Internal Medicine

Vitamin D in atherosclerosis and cardiovascular events.

In European heart journal ; h5-index 154.0

Both experimental and clinical findings linking vitamin D to cardiovascular (CV) risk have prompted consideration of its supplementation to improve overall health. Yet several meta-analyses do not provide support for the clinical effectiveness of this strategy. Meanwhile, the understanding of the roles of vitamin D in the pathophysiology of CV diseases has evolved. Specifically, recent work has revealed some non-classical pleiotropic effects of vitamin D, increasing the complexity of vitamin D signalling. Within particular microenvironments (e.g. dysfunctional adipose tissue and atherosclerotic plaque), vitamin D can act locally at cellular level through intracrine/autocrine/paracrine feedforward and feedback circuits. Within atherosclerotic tissues, 'local' vitamin D levels may influence relevant systemic consequences independently of its circulating pool. Moreover, vitamin D links closely to other signalling pathways of CV relevance including those driving cellular senescence, ageing, and age-related diseases-among them CV conditions. This review updates knowledge on vitamin D biology aiming to clarify the widening gap between experimental and clinical evidence. It highlights the potential reverse causation confounding correlation between vitamin D status and CV health, and the need to consider novel pathophysiological concepts in the design of future clinical trials that explore the effects of vitamin D on atherosclerosis and risk of CV events.

Carbone Federico, Liberale Luca, Libby Peter, Montecucco Fabrizio

2023-Mar-21

Adipose tissue, Atherosclerosis, Inflammation, Senescence, Vitamin D, Vitamin D receptor

General General

A Standardized Clinical Data Harmonization Pipeline for Scalable AI Application Deployment (FHIR-DHP): Validation and Usability Study.

In JMIR medical informatics ; h5-index 23.0

BACKGROUND : Increasing digitalization in the medical domain gives rise to large amounts of health care data, which has the potential to expand clinical knowledge and transform patient care if leveraged through artificial intelligence (AI). Yet, big data and AI oftentimes cannot unlock their full potential at scale, owing to nonstandardized data formats, lack of technical and semantic data interoperability, and limited cooperation between stakeholders in the health care system. Despite the existence of standardized data formats for the medical domain, such as Fast Healthcare Interoperability Resources (FHIR), their prevalence and usability for AI remain limited.

OBJECTIVE : In this paper, we developed a data harmonization pipeline (DHP) for clinical data sets relying on the common FHIR data standard.

METHODS : We validated the performance and usability of our FHIR-DHP with data from the Medical Information Mart for Intensive Care IV database.

RESULTS : We present the FHIR-DHP workflow in respect of the transformation of "raw" hospital records into a harmonized, AI-friendly data representation. The pipeline consists of the following 5 key preprocessing steps: querying of data from hospital database, FHIR mapping, syntactic validation, transfer of harmonized data into the patient-model database, and export of data in an AI-friendly format for further medical applications. A detailed example of FHIR-DHP execution was presented for clinical diagnoses records.

CONCLUSIONS : Our approach enables the scalable and needs-driven data modeling of large and heterogenous clinical data sets. The FHIR-DHP is a pivotal step toward increasing cooperation, interoperability, and quality of patient care in the clinical routine and for medical research.

Williams Elena, Kienast Manuel, Medawar Evelyn, Reinelt Janis, Merola Alberto, Klopfenstein Sophie Anne Ines, Flint Anne Rike, Heeren Patrick, Poncette Akira-Sebastian, Balzer Felix, Beimes Julian, von Bünau Paul, Chromik Jonas, Arnrich Bert, Scherf Nico, Niehaus Sebastian

2023-Mar-21

AI, AI application, FHIR, MIMIC IV, artificial intelligence, care, care unit, cooperation, data, data interoperability, data standardization pipeline, deployment, diagnosis, fast healthcare interoperability resources, medical information mart for intensive care, medical research, patient care, usability

Public Health Public Health

Heterogeneity in the response to n-3 polyunsaturated fatty acids.

In Current opinion in clinical nutrition and metabolic care

PURPOSE OF REVIEW : A central goal in the study of long chain n-3 polyunsaturated fatty acids (PUFA) is to translate findings from the basic sciences to the population level to improve human health and prevent chronic diseases. A tenet of this vision is to think in terms of precision medicine and nutrition, that is, stratification of individuals into differing groups that will have different needs across the lifespan for n-3 PUFAs. Therefore, there is a critical need to identify the sources of heterogeneity in the human population in the dietary response to n-3 PUFA intervention.

RECENT FINDINGS : We briefly review key sources of heterogeneity in the response to intake of long chain n-3 PUFAs. These include background diet, host genome, composition of the gut microbiome, and sex. We also discuss the need to integrate data from newer rodent models (e.g. population-based approaches), multi -omics, and analyses of big data using machine learning and data-driven cluster analyses.

SUMMARY : Accounting for vast heterogeneity in the human population, particularly with the use of big data integrated with preclinical evidence, will drive the next generation of precision nutrition studies and randomized clinical trials with long-chain n-3 PUFAs.

Shaikh Saame Raza, Bazinet Richard P

2023-Mar-21