On the Adoption of Modern Technologies to Fight the COVID-19 Pandemic: A Technical Synthesis of Latest Developments

COVID, Journal Year: 2023, Volume and Issue: 3(1), P. 90 - 123

Published: Jan. 16, 2023

In the ongoing COVID-19 pandemic, digital technologies have played a vital role to minimize spread of COVID-19, and control its pitfalls for general public. Without such technologies, bringing pandemic under would been tricky slow. Consequently, exploration status, devising appropriate mitigation strategies also be difficult. this paper, we present comprehensive analysis community-beneficial that were employed fight pandemic. Specifically, demonstrate practical applications ten major effectively served mankind in different ways during crisis. We chosen these based on their technical significance large-scale adoption arena. The selected are Internet Things (IoT), artificial intelligence(AI), natural language processing(NLP), computer vision (CV), blockchain (BC), federated learning (FL), robotics, tiny machine (TinyML), edge computing (EC), synthetic data (SD). For each technology, working mechanism, context challenges from perspective COVID-19. Our can pave way understanding roles COVID-19-fighting used future infectious diseases prevent global crises. Moreover, discuss heterogeneous significantly contributed addressing multiple aspects when fed aforementioned technologies. To best authors’ knowledge, is pioneering work transformative with broader coverage studies applications.

Language: Английский

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Time-Series Analysis and Healthcare Implications of COVID-19 Pandemic in Saudi Arabia

Healthcare, Journal Year: 2022, Volume and Issue: 10(10), P. 1874 - 1874

Published: Sept. 26, 2022

The first case of coronavirus disease 2019 (COVID-19) in Saudi Arabia was reported on 2 March 2020. Since then, it has progressed rapidly and the number cases grown exponentially, reaching 788,294 22 June 2022. Accurately analyzing predicting spread new COVID-19 is critical to develop a framework for universal pandemic preparedness as well mitigating disease's spread. To this end, main aim paper analyze historical data gathered from 2020 20 2022 second use collected forecasting trajectory order construct robust accurate models. best our knowledge, study that analyzes outbreak long period (more than two years). achieve aim, techniques analytics field, namely auto-regressive integrated moving average (ARIMA) statistical technique Prophet Facebook machine learning were investigated daily infections, recoveries deaths. Based performance metrics, both models found be time series considered (the coefficient determination example all more 0.96) with small superiority ARIMA model terms ability simplicity few hyper-parameters. findings have yielded realistic picture direction provide useful insights decision makers so prepared future evolution pandemic. In addition, results shown positive healthcare implications experience fighting relative efficiency taken measures.

Language: Английский

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A comparative study of three models to analyze the impact of air pollutants on the number of pulmonary tuberculosis cases in Urumqi, Xinjiang

PLoS ONE, Journal Year: 2023, Volume and Issue: 18(1), P. e0277314 - e0277314

Published: Jan. 17, 2023

In this paper, we separately constructed ARIMA, ARIMAX, and RNN models to determine whether there exists an impact of the air pollutants (such as PM2.5, PM10, CO, O3, NO2, SO2) on number pulmonary tuberculosis cases from January 2014 December 2018 in Urumqi, Xinjiang. addition, by using a new comprehensive evaluation index DISO compare performance three models, it was demonstrated that ARIMAX (1,1,2) × (0,1,1)12 + PM2.5 (lag = 12) model optimal one, which applied predict Urumqi 2019 2019. The predicting results were good agreement with actual shown obviously declined, indicated policies environmental protection universal health checkups have been very effective recent years.

Language: Английский

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Automatic discrimination between neuroendocrine carcinomas and grade 3 neuroendocrine tumors by deep learning of H&E images

Computers in Biology and Medicine, Journal Year: 2024, Volume and Issue: 184, P. 109443 - 109443

Published: Nov. 21, 2024

Neuroendocrine neoplasms (NENs) arise from diffuse neuroendocrine cells and are categorized as either well-differentiated less proliferative Tumors (NETs), divided into low (G1), middle (G2), high grades (G3), or poorly differentiated, more Carcinomas (NECs). Low-grade NENs typically necessitate surgical intervention, whereas high-grade ones often require chemotherapy. However, low-grade may exhibit aggressive behavior. Therefore, it is crucial to precisely refine the diagnosis of NENs. This refinement achievable when differentiation/non-differentiation evident Ki-67 mitosis index low. The challenge arises in cases morphologically undifferentiated instances with a percentage and/or mitotic index. To address this challenge, we developed Deep Learning (DL) system named NEToC, designed differentiate between NETs NECs using exclusively morphological information immunohistochemistry images, without relying on assessments. NEToC was 95 NEN period 2015 2018 at Parc Tauli Hospital Spain, comprising 588 images. Implemented Graphical User Interface (GUI) system, intended for deployment pathological departments hospitals perform federated supervision. We tested performance 119 images that were not used during Artificial Neural Network (ANN) training phase, evaluated its robustness across various resolutions: 64 × 64, 128 128, 256 256, 512 pixels. achieved accuracies these resolutions 74 %, 98 100 respectively, an underrepresented NET G3 experiment, 66 89 % 94 represented experiment. Based several measured metrics, optimal resolution appears be pixels, considering computational resources accuracy requirements. found 256-pixel robust classify classes learning phase. These results imply discriminate Grade 3 needs resolved regions pixel no than 4 μm/pixel. Most misclassifications false negatives, where G1-type erroneously classified NEC-type. Our demonstrate DL-based diagnostic algorithm provides accurate physicians face challenges. has been initially trained gastrointestinal Since morphology does change among different organs, use can extrapolated organs. facilitates supervision, allowing pathologists collect interchangeable files based classification predictions. easy-to-use, adaptable software integrates multiple ANNs improve standardization diagnosis, opening up possibilities combining DL histological supervision systems. A future goal only NETs, but also three-tier (NET G1, G2, G3) solely tissue differentiation information.

Language: Английский

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COVID-19 Hotspot Mapping and Prediction in Aizawl District of Mizoram: a Hotspot and SEIR Model-Based Analysis

Sankhya A, Journal Year: 2023, Volume and Issue: 86(1), P. 1 - 26

Published: July 10, 2023

Language: Английский

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The Assessment of Digitalisation Among Malaysian Public Listed Companies in Consumer Product and Services Industries Using Business Process Management in the Pre- and Post-COVID-19 Situations

International Journal of Academic Research in Business and Social Sciences, Journal Year: 2022, Volume and Issue: 12(12)

Published: Dec. 5, 2022

The adverse impacts of COVID-19 towards the performance business sector have forced companies around globe to realise importance digitalisation in strategic planning. Subsequently, sustaining bottom-line has become a major driving factor for integrate into operations addressing and overcoming negative effects especially on key financial matters such as company's sales expenses. To date, there is dearth studies that measure what extent consumer product service applied digitalisation. Therefore, using content analysis selected companies’ disclosures their annual reports, this present study aimed assess how much Malaysian public listed from sectors embraced assessment those was done Business Process Management (BPM) Model involving two dimensions: ordinary dynamic capabilities. findings suggest application higher after pandemic. crucial relevant it does not only substantiate existing literature related digitalisation, but also provides latest insights evidence activities among Malaysia. This signifies address disruptions global economy.

Language: Английский

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