Digital Health and Healthcare Quality: A Primer on the Evolving 4th Industrial Revolution

Otokiti, Ahmed

doi:10.5772/intechopen.94054

Cited by 5 publications

(3 citation statements)

References 54 publications

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“…There is also a lack of necessary mandate of using AI in clinical application to seek evidence-based medical practices, especially in the era of 4IR. [ 23 ] Although in recent time, vaccination initiative has started, several persons are still getting infected even after receiving vaccine. Hence, to start treatment early and to prevent community transmission further, still there is a demand of cheap and easier diagnostic procedure of COVID-19 infection.…”

Section: Discussionmentioning

confidence: 99%

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Development of a Fast Fourier Transform-based Analytical Method for COVID-19 Diagnosis from Chest X-Ray Images Using GNU Octave

Majumder

2022

Journal of Medical Physics

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Purpose: Many artificial intelligence-based computational procedures are developed to diagnose COVID-19 infection from chest X-ray (CXR) images, as diagnosis by CXR imaging is less time consuming and economically cheap compared to other detection procedures. Due to unavailability of skilled computer professionals and high computer architectural resource, majority of the employed methods are difficult to implement in rural and poor economic settings. Majority of such reports are devoid of codes and ignores related diseases (pneumonia). The absence of codes makes limitation in applying them widely. Hence, validation testing followed by evidence-based medical practice is difficult. The present work was aimed to develop a simple method that requires a less computational expertise and minimal level of computer resource, but with statistical inference. Materials and Methods: A Fast Fourier Transform-based (FFT) method was developed with GNU Octave, a free and open-source platform. This was employed to the images of CXR for further analysis. For statistical inference, two variables, i.e., the highest peak and number of peaks in the FFT distribution plot were considered. Results: The comparison of mean values among different groups (normal, COVID-19, viral, and bacterial pneumonia [BP]) showed statistical significance, especially when compared to normal, except between viral and BP groups. Conclusion: Parametric statistical inference from our result showed high level of significance ( P < 0.001). This is comparable to the available artificial intelligence-based methods (where accuracy is about 94%). Developed method is easy, availability with codes, and requires a minimal level of computer resource and can be tested with a small sample size in different demography, and hence, be implemented in a poor socioeconomic setting.

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Section: Discussionmentioning

confidence: 99%

“…[ 22 ] Moreover, AI-based methods are still not included in the evidence-based clinical practices. [ 23 ] Such limitations may restrict the use of AI-based method in a small demographic region. In majority of the cases, for COVID-19 detection from X-ray images by computational methods, codes are not available.…”

Section: Introductionmentioning

confidence: 99%

Development of a Fast Fourier Transform-based Analytical Method for COVID-19 Diagnosis from Chest X-Ray Images Using GNU Octave

Majumder

2022

Journal of Medical Physics

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“…Satu pandangan dari banyak aktivitas data mining skala besar adalah bahwa mereka terutama merupakan pemfilteran dan reduksi data. Meskipun beberapa subdisiplin statistik telah memeriksa kasus khusus dari masalah ini, sebagian besar pekerjaan pada deteksi pola hingga saat ini bersifat komputasi, dengan penekanan pada algoritma (Umar Otokiti, 2022).…”

Section: Data Miningunclassified

Penerapan Visualisasi Data Terhadap Klasifikasi Tindak Kriminal Di Indonesia

Madyatmadja¹,

Ridho

Pratama

et al. 2022

j.nanotechnol.inf.

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Crime still occurs in every region in Indonesia. Various classifications of crimes that occur and cause unrest for people in every region in Indonesia. The purpose of this study is to analyze and visualize data on crimes that occur in every region in Indonesia so as to facilitate the Indonesian government in making decisions. The method used for this research is the clustering method. The clustering stage is carried out by grouping data on crimes that occur in Indonesia which are classified from each region. The results of the data that have been visualized show that the crime rate in each area is different according to the classification of crime, so it is necessary to increase security in each area that has a level of criminality data according to the classification of crime.

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Mathematical Oncology to Cancer Systems Medicine: Translation from Academic Pursuit to Individualized Therapy with MORA

Majumder

2023

CCTR

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Aim & Objective: This article is aimed to understand the gradual development of cancer systems medicine and how this provides a better therapeutic strategy (in terms of drug selection, dose and duration) and patients care. Hence, this study is focused to understand the need and the evolving nature of the analytical models for the assessment of the outcome of different cancer therapeutics. Background: Presently, cancer is viewed from a quantitative standpoint; hence, several analytical models on different cancers have developed. From the information of cancer development to therapeutic advantage, mathematical oncology has contributed significantly. With a fewer number of variables, models in this area have successfully synchronized the model output with real-life dynamical data. However, with the availability of large scale data for different cancers, systems biology has gained importance. It provides biomedical insights among a large number of variables. And to get information for clinically relevant variables especially, the controlling variable(s), cancer systems medicine is suggested. Methods: In this article, we have reviewed the gradual development of the field from mathematical oncology to cancer systems biology to cancer systems medicine. An intensive search with PubMed, IEEE Xplorer and Google for cancer model, analytical model and cancer systems biology was made and the latest developments have been noted. Results: Gradual development of cancer systems biology entails the importance of the development of models towards a unified model of cancer treatment. For this, the model should be flexible so that different types of cancer and/or its therapy can be included within the same model. With the existing knowledge, relevant variables are included in the same model, followed by simulation studies that will enrich the knowledge base further. Such a deductive approach in the modelling and simulations efforts can help to tackle the adversity of individual cancer cases in future. This approach is indeed important to encompass the fourth industrial revolution in health sector. Conclusion: Towards the development of a unified modelling effort, a multi-scale modelling approach could be suitable; so that different researchers across the globe can add their contribution to enrich the same model. Moreover, with this, the identification of controlling variables may be possible. Towards this goal, middle-out rationalist approach (MORA) is working on analytical models for cancer treatment.

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Digital Health and Healthcare Quality: A Primer on the Evolving 4th Industrial Revolution

Cited by 5 publications

References 54 publications

Development of a Fast Fourier Transform-based Analytical Method for COVID-19 Diagnosis from Chest X-Ray Images Using GNU Octave

Development of a Fast Fourier Transform-based Analytical Method for COVID-19 Diagnosis from Chest X-Ray Images Using GNU Octave

Penerapan Visualisasi Data Terhadap Klasifikasi Tindak Kriminal Di Indonesia

Mathematical Oncology to Cancer Systems Medicine: Translation from Academic Pursuit to Individualized Therapy with MORA

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