The Potential of Big Data Research in HealthCare for Medical Doctors’ Learning

Au‐Yong‐Oliveira, Manuel; Pesqueira, António Miguel; Sousa, Maria José; Mas, Francesca Dal; Soliman, Mohammad

doi:10.1007/s10916-020-01691-7

Cited by 38 publications

(17 citation statements)

References 59 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Education is the healthcare professional’s main source of preparedness. [ 31 ] Pharmacists expressed having inadequate levels of preparedness in their education. In the short term, useful lessons about pharmacy practice can be learned from previous viral outbreaks in LMICs such as the Ebola in Nigeria, [ 32 ] and by ensuring the proactive gathering and sharing of new and continuously evolving information about COVID-19 from authorities in more developed countries, such as Australia.…”

Section: Discussionmentioning

confidence: 99%

Community pharmacy practice related to the COVID-19 pandemic: barriers and facilitators

Bahlol

Tran

Dewey

2022

International Journal of Pharmacy Practice

View full text Add to dashboard Cite

Background Community pharmacies provide an important healthcare service. Their significant value has been further highlighted during the COVID-19 pandemic crisis. Objectives To identify and categorize potential barriers and facilitators to the role of community pharmacists during the pandemic and their association with demographic factors. Methods A cross-sectional survey of community pharmacists was conducted using a self-administered questionnaire during April 2020 across all regions of Egypt. Key findings Respondents (n = 1018; 98.4% response rate) revealed practical and psychological barriers, including inadequate levels of pandemic preparedness (mean 61.43%; ±SD 0.47), inadequate working environments (mean 56.23%; ±SD 0.49) and uncooperative behaviour from stakeholders (mean 65.3%; ±SD 0.47).The majority of respondents emphasized the universal, region-independent necessity for facilitators, including the availability of timely (94.9%) guidance (97.4%) published by the Egyptian healthcare authority (94.6%), in electronic format (82.1%), through smartphone application (80.0%) and the provision of a dedicated telephone hotline (89.5%). Furthermore, authorities must use the media to manage public perceptions (97.2%) and increase public trust (94.8%) towards the pharmacist. Conclusions The barriers and facilitators identified herein could improve service provision in an integrated manner by overcoming the reported inadequate level of preparedness (barrier) through the provision of electronic guidance (facilitator), and the use of the media in managing public perceptions and trust (facilitators) to reduce the panic that negatively affects the working environment (barrier) for pharmacy staff. The varied level of healthcare authority cooperation reported in many regions requires further investigation.

show abstract

Section: Discussionmentioning

confidence: 99%

Community pharmacy practice related to the COVID-19 pandemic: barriers and facilitators

Bahlol

Tran

Dewey

2022

International Journal of Pharmacy Practice

View full text Add to dashboard Cite

show abstract

“…In the era of precision medicine research, integrating a wide variety of data from different sources is of key importance for the complete take charge of the patients [ 90 ]. The proposed retrospective project will be the first to explore the application of AI methods to CDH.…”

Section: Discussionmentioning

confidence: 99%

A maChine and deep Learning Approach to predict pulmoNary hyperteNsIon in newbornS with congenital diaphragmatic Hernia (CLANNISH): Protocol for a retrospective study

et al. 2021

View full text Add to dashboard Cite

Introduction Outcome predictions of patients with congenital diaphragmatic hernia (CDH) still have some limitations in the prenatal estimate of postnatal pulmonary hypertension (PH). We propose applying Machine Learning (ML), and Deep Learning (DL) approaches to fetuses and newborns with CDH to develop forecasting models in prenatal epoch, based on the integrated analysis of clinical data, to provide neonatal PH as the first outcome and, possibly: favorable response to fetal endoscopic tracheal occlusion (FETO), need for Extracorporeal Membrane Oxygenation (ECMO), survival to ECMO, and death. Moreover, we plan to produce a (semi)automatic fetus lung segmentation system in Magnetic Resonance Imaging (MRI), which will be useful during project implementation but will also be an important tool itself to standardize lung volume measures for CDH fetuses. Methods and analytics Patients with isolated CDH from singleton pregnancies will be enrolled, whose prenatal checks were performed at the Fetal Surgery Unit of the Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico (Milan, Italy) from the 30th week of gestation. A retrospective data collection of clinical and radiological variables from newborns’ and mothers’ clinical records will be performed for eligible patients born between 01/01/2012 and 31/12/2020. The native sequences from fetal magnetic resonance imaging (MRI) will be collected. Data from different sources will be integrated and analyzed using ML and DL, and forecasting algorithms will be developed for each outcome. Methods of data augmentation and dimensionality reduction (feature selection and extraction) will be employed to increase sample size and avoid overfitting. A software system for automatic fetal lung volume segmentation in MRI based on the DL 3D U-NET approach will also be developed. Ethics and dissemination This retrospective study received approval from the local ethics committee (Milan Area 2, Italy). The development of predictive models in CDH outcomes will provide a key contribution in disease prediction, early targeted interventions, and personalized management, with an overall improvement in care quality, resource allocation, healthcare, and family savings. Our findings will be validated in a future prospective multicenter cohort study. Registration The study was registered at ClinicalTrials.gov with the identifier NCT04609163.

show abstract

“…MHD group: ① Infection control management: strengthen the environmental management of departments, strictly limit the number of visitors in departments, regularly disinfect the items and environment in departments every day, keep indoor ventilation, strictly classify the medical wastes by nurses, carry out citric acid/sodium hypochlorite and heat elimination after dialysis, and destroy the used disposable materials in time. ② Infection prevention knowledge training: the head nurse regularly organizes department workers to participate in nursing knowledge training on hemodialysis infection control and regularly carries out technical assessment, so as to continuously improve nurses' subjective awareness of infection control and aseptic concept [ 10 ]. When entering the dialysis room during daily work, the medical staff are required to change sterile clothes and shoes, strictly abide by the dialysis treatment process, and standardize the nursing operation.…”

Section: Methodsmentioning

confidence: 99%

Study on Ultrasonic Imaging of Nursing Care for Preventing and Treating Clinical Infection of Hemodialysis Patients Based on Smart Medical Big Data

Wen

Yanjun

2021

Contrast Media & Molecular Imaging

View full text Add to dashboard Cite

The ultrasonic imaging research of nursing care for preventing and treating clinical infection of hemodialysis patients based on smart medical big data is studied. 100 hemodialysis patients were selected from May 2019 to May 2020. The patients were randomly divided into the observation group and routine group with 50 cases in each group. The PWV of common carotid artery was measured by ultrasonic rapid imaging technology, including BS value at the beginning of systole and ES value at the end of systole. According to the effect of preventive nursing intervention of intelligent medical treatment, the MHD group adopted preventive nursing intervention, while the routine group adopted traditional nursing service. The infection rate and quality of life score of patients in both groups were evaluated. The results showed that there were significant differences in BS and ES values between the MHD group and PWV in the normal group ( P < 0.05 ). There was no significant difference in BS value and ES value between MHD patients with plaque and those without plaque ( P > 0.05 ). It is proved that the ultrafast ultrasound imaging technology is safe, simple, noninvasive, nonradioactive, and fast and can automatically and accurately detect carotid PWV. It is expected to become a new imaging method for quantitative evaluation of arteriosclerosis degree in MHD patients. Preventive nursing intervention can reduce the incidence of infection in hemodialysis patients and improve their quality of life. Smart medical treatment has brought us a lot of convenience. As patients, we should change our concept, actively participate in it, and contribute to the development of smart medical treatment.

show abstract

The Potential of Big Data Research in HealthCare for Medical Doctors’ Learning

Cited by 38 publications

References 59 publications

Community pharmacy practice related to the COVID-19 pandemic: barriers and facilitators

Community pharmacy practice related to the COVID-19 pandemic: barriers and facilitators

A maChine and deep Learning Approach to predict pulmoNary hyperteNsIon in newbornS with congenital diaphragmatic Hernia (CLANNISH): Protocol for a retrospective study

Study on Ultrasonic Imaging of Nursing Care for Preventing and Treating Clinical Infection of Hemodialysis Patients Based on Smart Medical Big Data

Contact Info

Product

Resources

About