Beyond Data: Actionable AI - Review of the 2023 Fall Conference of the Korean Society of Medical Informatics
Healthc Inform Res. 2024 Jan;30(1):1-2. doi: 10.4258/hir.2024.30.1.1. Epub 2024 Jan 31.NO ABSTRACTPMID:38359844 | PMC:PMC10879822 | DOI:10.4258/hir.2024.30.1.1 (Source: Healthcare Informatics Research)
Source: Healthcare Informatics Research - February 15, 2024 Category: Information Technology Authors: Younghee Lee Taehoon Ko Kwangmo Yang Source Type: research

Survey of Medical Applications of Federated Learning
CONCLUSIONS: FL in the medical domain appears to be in its early stages, with most research using open data and focusing on specific data types and diseases for performance verification purposes. Nonetheless, medical FL research is anticipated to be increasingly applied and to become a vital component of multi-institutional research.PMID:38359845 | PMC:PMC10879826 | DOI:10.4258/hir.2024.30.1.3 (Source: Healthcare Informatics Research)
Source: Healthcare Informatics Research - February 15, 2024 Category: Information Technology Authors: Geunho Choi Won Chul Cha Se Uk Lee Soo-Yong Shin Source Type: research

Review of Qualitative Research Methods in Health Information System Studies
CONCLUSIONS: Reports on the qualitative research process should include descriptions of researchers' reflections and ethical considerations, which are meaningful for strengthening the rigor and credibility of qualitative research. Based on these discussions, we suggest guidance for conducting ethical, feasible, and reliable qualitative research on HISs in hospital settings.PMID:38359846 | PMC:PMC10879827 | DOI:10.4258/hir.2024.30.1.16 (Source: Healthcare Informatics Research)
Source: Healthcare Informatics Research - February 15, 2024 Category: Information Technology Authors: Kyoungsoo Park Woojong Moon Source Type: research

Impact of the Lightwave Health Information Management Software on the Dimensions of Quality of Healthcare Data
CONCLUSIONS: LHIMS must be upgraded to include more decision support systems and additional add-ons such as patients' radiological reports, and laboratory results must be readily available on LHIMS to make patient health data more comprehensive.PMID:38359847 | PMC:PMC10879824 | DOI:10.4258/hir.2024.30.1.35 (Source: Healthcare Informatics Research)
Source: Healthcare Informatics Research - February 15, 2024 Category: Information Technology Authors: Charles Nana Agyemang Amoateng Emmanuel Kusi Achampong Source Type: research

Deep Learning Model and its Application for the Diagnosis of Exudative Pharyngitis
CONCLUSIONS: We trained a deep learning model based on EfficientNetB0 that can diagnose exudative pharyngitis. Our model was able to achieve the highest accuracy, at 95.5%, out of all previous studies that used machine learning for the diagnosis of exudative pharyngitis. We have deployed the model on a web application that can be used to augment the doctor's diagnosis of exudative pharyngitis.PMID:38359848 | PMC:PMC10879828 | DOI:10.4258/hir.2024.30.1.42 (Source: Healthcare Informatics Research)
Source: Healthcare Informatics Research - February 15, 2024 Category: Information Technology Authors: Seo Yi Chng Paul Jie Wen Tern Matthew Rui Xian Kan Lionel Tim-Ee Cheng Source Type: research

Technological Challenges and Solutions in Emergency Remote Teaching for Nursing: An International Cross-Sectional Survey
CONCLUSIONS: Our findings can help advance nursing education. Nevertheless, collaborative efforts from all stakeholders are essential to address current challenges, achieve digital equity, and develop a standardized curriculum for nursing education.PMID:38359849 | PMC:PMC10879829 | DOI:10.4258/hir.2024.30.1.49 (Source: Healthcare Informatics Research)
Source: Healthcare Informatics Research - February 15, 2024 Category: Information Technology Authors: Eunjoo Jeon Laura-Maria Peltonen Lorraine J Block Charlene Ronquillo Jude L Tayaben Raji Nibber Lisiane Pruinelli Erika Lozada Perezmitre Janine Sommer Maxim Topaz Gabrielle Jacklin Eler Henrique Yoshikazu Shishido Shanti Wardaningsih Sutantri Sutantri Sa Source Type: research

Prediction of Cervical Cancer Patients' Survival Period with Machine Learning Techniques
CONCLUSIONS: Machine learning demonstrated the ability to provide high-accuracy predictions of survival periods in both classification and regression problems. This suggests its potential use as a decision-support tool in the process of treatment planning and resource allocation for each patient.PMID:38359850 | PMC:PMC10879821 | DOI:10.4258/hir.2024.30.1.60 (Source: Healthcare Informatics Research)
Source: Healthcare Informatics Research - February 15, 2024 Category: Information Technology Authors: Intorn Chanudom Ekkasit Tharavichitkul Wimalin Laosiritaworn Source Type: research

Prediction of Diabetes Using Data Mining and Machine Learning Algorithms: A Cross-Sectional Study
CONCLUSIONS: A gradient boosted decision tree model accurately identified the most important risk factors related to diabetes. Age, waist-to-hip ratio, body mass index, and systolic blood pressure were the most important risk factors for diabetes, respectively. This model can support planning for diabetes management and prevention.PMID:38359851 | PMC:PMC10879823 | DOI:10.4258/hir.2024.30.1.73 (Source: Healthcare Informatics Research)
Source: Healthcare Informatics Research - February 15, 2024 Category: Information Technology Authors: Hassan Shojaee-Mend Farnia Velayati Batool Tayefi Ebrahim Babaee Source Type: research

Fostering Digital Health in Universities: An Experience of the First Junior Scientific Committee of the Brazilian Congress of Health Informatics
CONCLUSIONS: Forming a JSC proved to be a valuable tool to foster DH, particularly due to the valuable interactions it facilitated between esteemed professionals and students. It also supports the cultivation of leadership skills in DH, a field that has not yet received the recognition it deserves.PMID:38359852 | PMC:PMC10879825 | DOI:10.4258/hir.2024.30.1.83 (Source: Healthcare Informatics Research)
Source: Healthcare Informatics Research - February 15, 2024 Category: Information Technology Authors: Alexandre Negrao Pantaleao Anna Lu ísa Mennitti Felipe Baptista Brunheroto Vit ória Stavis Laura Teresa Ricoboni Victor Augusto Fonseca de Castro Ollivia Frederigue Ferreira Eura Martins Lage Deborah Ribeiro Carvalho Anita Maria da Rocha Fernandes Julia Source Type: research

Beyond Data: Actionable AI - Review of the 2023 Fall Conference of the Korean Society of Medical Informatics
Healthc Inform Res. 2024 Jan;30(1):1-2. doi: 10.4258/hir.2024.30.1.1. Epub 2024 Jan 31.NO ABSTRACTPMID:38359844 | PMC:PMC10879822 | DOI:10.4258/hir.2024.30.1.1 (Source: Healthcare Informatics Research)
Source: Healthcare Informatics Research - February 15, 2024 Category: Information Technology Authors: Younghee Lee Taehoon Ko Kwangmo Yang Source Type: research

Survey of Medical Applications of Federated Learning
CONCLUSIONS: FL in the medical domain appears to be in its early stages, with most research using open data and focusing on specific data types and diseases for performance verification purposes. Nonetheless, medical FL research is anticipated to be increasingly applied and to become a vital component of multi-institutional research.PMID:38359845 | PMC:PMC10879826 | DOI:10.4258/hir.2024.30.1.3 (Source: Healthcare Informatics Research)
Source: Healthcare Informatics Research - February 15, 2024 Category: Information Technology Authors: Geunho Choi Won Chul Cha Se Uk Lee Soo-Yong Shin Source Type: research

Review of Qualitative Research Methods in Health Information System Studies
CONCLUSIONS: Reports on the qualitative research process should include descriptions of researchers' reflections and ethical considerations, which are meaningful for strengthening the rigor and credibility of qualitative research. Based on these discussions, we suggest guidance for conducting ethical, feasible, and reliable qualitative research on HISs in hospital settings.PMID:38359846 | PMC:PMC10879827 | DOI:10.4258/hir.2024.30.1.16 (Source: Healthcare Informatics Research)
Source: Healthcare Informatics Research - February 15, 2024 Category: Information Technology Authors: Kyoungsoo Park Woojong Moon Source Type: research

Impact of the Lightwave Health Information Management Software on the Dimensions of Quality of Healthcare Data
CONCLUSIONS: LHIMS must be upgraded to include more decision support systems and additional add-ons such as patients' radiological reports, and laboratory results must be readily available on LHIMS to make patient health data more comprehensive.PMID:38359847 | PMC:PMC10879824 | DOI:10.4258/hir.2024.30.1.35 (Source: Healthcare Informatics Research)
Source: Healthcare Informatics Research - February 15, 2024 Category: Information Technology Authors: Charles Nana Agyemang Amoateng Emmanuel Kusi Achampong Source Type: research

Deep Learning Model and its Application for the Diagnosis of Exudative Pharyngitis
CONCLUSIONS: We trained a deep learning model based on EfficientNetB0 that can diagnose exudative pharyngitis. Our model was able to achieve the highest accuracy, at 95.5%, out of all previous studies that used machine learning for the diagnosis of exudative pharyngitis. We have deployed the model on a web application that can be used to augment the doctor's diagnosis of exudative pharyngitis.PMID:38359848 | PMC:PMC10879828 | DOI:10.4258/hir.2024.30.1.42 (Source: Healthcare Informatics Research)
Source: Healthcare Informatics Research - February 15, 2024 Category: Information Technology Authors: Seo Yi Chng Paul Jie Wen Tern Matthew Rui Xian Kan Lionel Tim-Ee Cheng Source Type: research

Technological Challenges and Solutions in Emergency Remote Teaching for Nursing: An International Cross-Sectional Survey
CONCLUSIONS: Our findings can help advance nursing education. Nevertheless, collaborative efforts from all stakeholders are essential to address current challenges, achieve digital equity, and develop a standardized curriculum for nursing education.PMID:38359849 | PMC:PMC10879829 | DOI:10.4258/hir.2024.30.1.49 (Source: Healthcare Informatics Research)
Source: Healthcare Informatics Research - February 15, 2024 Category: Information Technology Authors: Eunjoo Jeon Laura-Maria Peltonen Lorraine J Block Charlene Ronquillo Jude L Tayaben Raji Nibber Lisiane Pruinelli Erika Lozada Perezmitre Janine Sommer Maxim Topaz Gabrielle Jacklin Eler Henrique Yoshikazu Shishido Shanti Wardaningsih Sutantri Sutantri Sa Source Type: research