A Digital Health System for Disease Analytics

Leung, Carson K.; Fung, Daryl L. X.; Daniel, Thanh Huy; Souza, Joglas; Tran, Nguyen

doi:10.1109/icdh52753.2021.00019

Cited by 11 publications

(4 citation statements)

References 55 publications

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“…As a result, it aids in the prevention and treatment of the condition. Generally, disease refers to disorders that cause discomfort, dysfunction, distress, or death in infected people and their close contacts (Leung et al, 2021 ). Additionally, the development of a social DA pipeline to enable analysts to investigate suspected online radicalization using social data is another example of the utility of DS in healthcare.…”

Section: Healthcare Analyticsmentioning

confidence: 99%

“…Existing efforts on sensing, tracking, testing, diagnosis, therapy, and prognosis include, for example, the imaging-based diagnosis of COVID-19, which employs many Chest-computed Tomography (CT) scan pictures for training. However, these images can be expensive to develop, and the technology used to create them (e.g., CT scanners) may not be commonly available (Leung et al, 2021 ).…”

Section: Healthcare Analyticsmentioning

confidence: 99%

“…Data analytics (DA), data mining, databases, high-performance computing, cloud computing, machine learning (ML), mathematical and statistical modeling, and visualization are examples of the tools and technologies used in DS. The aforementioned DS techniques can be applied to various datasets, e.g., biodiversity, census, diseases and healthcare, environment, genomics, social networks, transportation, and the web, for visualization, analysis, and interpretation (Leung et al, 2021 ). Most of these technological advances rely on vast amounts of data, the so-called big data (BD).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Healthcare analytics—A literature review and proposed research agenda

Elragal,

Habibipour

2023

Front. Big Data

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This research addresses the demanding need for research in healthcare analytics, by explaining how previous studies have used big data, AI, and machine learning to identify, address, or solve healthcare problems. Healthcare science methods are combined with contemporary data science techniques to examine the literature, identify research gaps, and propose a research agenda for researchers, academic institutions, and governmental healthcare organizations. The study contributes to the body of literature by providing a state-of-the-art review of healthcare analytics as well as proposing a research agenda to advance the knowledge in this area. The results of this research can be beneficial for both healthcare science and data science researchers as well as practitioners in the field.

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Section: Healthcare Analyticsmentioning

confidence: 99%

Section: Healthcare Analyticsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Healthcare analytics—A literature review and proposed research agenda

Elragal,

Habibipour

2023

Front. Big Data

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“…Computed Tomography is the standard radiological study to diagnose acute appendicitis 10 . Computed tomography (CT) is unavailable, especially in rural areas 11 . To reduce negative appendectomies and delay in diagnosis of complicated appendicitis there arises a gap in available diagnostic markers.…”

Section: Introductionmentioning

confidence: 99%

Diagnostic Accuracy Of Hyperbilirubinemia In Acute Appendicitis

Baseer,

Rehman,

Kalwar

et al. 2023

JRMC

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Objective: To determine the diagnostic accuracy of serum Bilirubin in cases of acute appendicitis keeping the histopathological findings as Gold standard. Study Design: Cross sectional validation study. Place and Duration of the Study: Surgical Unit, Sheikh Khalifa Bin Zayed Al-Nayhan Hospital (Combined Military Hospital), Rawalakot, Azad Kashmir, from Jan 2022 to June 2022. Methodology: A total of 380 patients aged between 18 to 65 years, who matched the inclusion and exclusion criteria suspected of acute appendicitis were included. Serum Bilirubin level was noted. Appendectomy was done. Specimen of appendix was sent for histopathology for confirmation of the diagnosis. Results: In our study, mean age of the patients was 34.015 with a standard deviation of 13.32. 65% (n=247) of the patients were males and 35% (n=133) were females. Frequency of acute appendicitis on histopathology was 82.89% (n=315) while 17.1% (n=65) had no findings of the disease. Validity of serum Bilirubin in diagnosing appendicitis using histopathology showed 57.36% (n=218) were true positive, 2.1% (n=8) were false positive, 15% (n=57) were true negative and 25.52 %( n=97) were false negative. Specificity, sensitivity, negative predictive value, positive predictive value, accuracy rate, positive likelihood ratio and negative likelihood ratio were 87.69%, 69.20%, 37.01%, 96.46%, 72.36%, 5.62 and 0.35 respectively. Conclusion: Serum Bilirubin is a useful marker for diagnosing the acute appendicitis and can be used as a good alternative diagnostic modality in suspected cases of acute appendicitis.

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Healthcare Analytics: Conceptualizing a Research Agenda

Elragal,

Habibipour

2024

Procedia Computer Science

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A Digital Health System for Disease Analytics

Cited by 11 publications

References 55 publications

Healthcare analytics—A literature review and proposed research agenda

Healthcare analytics—A literature review and proposed research agenda

Diagnostic Accuracy Of Hyperbilirubinemia In Acute Appendicitis

Healthcare Analytics: Conceptualizing a Research Agenda

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