A comparison of machine learning algorithms in predicting COVID-19 prognostics DOI Creative Commons
Serpil Üstebay, Abdurrahman Sarmış, Gülsüm Kübra Kaya

и другие.

Internal and Emergency Medicine, Год журнала: 2022, Номер 18(1), С. 229 - 239

Опубликована: Сен. 18, 2022

ML algorithms are used to develop prognostic and diagnostic models so support clinical decision-making. This study uses eight supervised predict the need for intensive care, intubation, mortality risk COVID-19 patients. The two datasets: (1) patient demographics data (n = 11,712), (2) demographics, data, blood test results 602) developing prediction models, understanding most significant features, comparing performances of different algorithms. Experimental findings showed that all reported an AUROC value over 0.92, in which extra tree CatBoost classifiers were often outperformed (AUROC 0.94). revealed features C-reactive protein, ratio lymphocytes, lactic acid, serum calcium have a substantial impact on predictions. provides evidence tree-based predicting prognosis health care.

Язык: Английский

Worker and workplace Artificial Intelligence (AI) coexistence: Emerging themes and research agenda DOI Creative Commons
Araz Zirar, Syed Imran Ali, Nazrul Islam

и другие.

Technovation, Год журнала: 2023, Номер 124, С. 102747 - 102747

Опубликована: Март 15, 2023

Workplace Artificial Intelligence (AI) helps organisations increase operational efficiency, enable faster-informed decisions, and innovate products services. While there is a plethora of information about how AI may provide value to workplaces, research on workers can coexist in workplaces evolving. It critical explore emerging themes agendas understand the trajectory scholarly this area. This study's overarching question will with workplaces. A search protocol was employed find relevant articles Scopus, ProQuest, Web Science databases based appropriate specific keywords article inclusion exclusion criteria. We identified four themes: (1) Workers' distrust workplace stems from perceiving it as job threat, (2) entices worker-AI interactions by offering augment worker abilities, (3) coexistence require workers' technical, human, conceptual skills, (4) Workers need ongoing reskilling upskilling contribute symbiotic relationship AI. then developed propositions questions for future research. review makes contributions: argues that an existential argument better explains AI, gathers required skills groups them into suggests technical benefit but cannot outweigh human offers 20 evidence-informed guide inquiries.

Язык: Английский

Процитировано

149

Applications of machine learning in thermochemical conversion of biomass-A review DOI
Muzammil Khan, Salman Raza Naqvi, Zahid Ullah

и другие.

Fuel, Год журнала: 2022, Номер 332, С. 126055 - 126055

Опубликована: Сен. 24, 2022

Язык: Английский

Процитировано

146

The applications of MCDM methods in COVID-19 pandemic: A state of the art review DOI
Alireza Sotoudeh-Anvari

Applied Soft Computing, Год журнала: 2022, Номер 126, С. 109238 - 109238

Опубликована: Июнь 30, 2022

Язык: Английский

Процитировано

140

The Role of Artificial Intelligence and Machine Learning Amid the COVID-19 Pandemic: What Lessons Are We Learning on 4IR and the Sustainable Development Goals DOI Open Access
David Mhlanga

International Journal of Environmental Research and Public Health, Год журнала: 2022, Номер 19(3), С. 1879 - 1879

Опубликована: Фев. 8, 2022

The COVID-19 pandemic came with disruptions in every aspect of human existence, all the sectors economies world affected greatly. In health sector, halted and reversed progress subsequently shortened life expectancy, especially developing underdeveloped nations. On other hand, machine learning artificial intelligence contributed a great deal to handling globally. Therefore, current study aimed assess role played by addressing dangers posed pandemic, as well extrapolate lessons on fourth industrial revolution sustainable development goals. Using qualitative content analysis, results indicated that an important response challenges pandemic. Artificial intelligence, learning, various digital communication tools through telehealth performed meaningful roles scaling customer communications, provided platform for understanding how spreads, sped up research treatment COVID-19, among notable achievements. we draw from this is that, despite rise number unintended consequences technology revolution, motivates us conclude governments must build trust these technologies, address problems going forward, ensure goals related good wellbeing are achieved.

Язык: Английский

Процитировано

96

Artificial neural networks for the prediction of biochar yield: A comparative study of metaheuristic algorithms DOI Creative Commons
Muzammil Khan, Zahid Ullah, Ondřej Mašek

и другие.

Bioresource Technology, Год журнала: 2022, Номер 355, С. 127215 - 127215

Опубликована: Апрель 23, 2022

In this study, an integrated framework of artificial neural networks (ANNs) and metaheuristic algorithms have been developed for the prediction biochar yield using biomass characteristics pyrolysis process conditions. Comparative analysis six different was performed to optimize ANN architecture select important features. The results suggested that model coupled with Rao-2 algorithm outperformed (R2 ∼ 0.93, RMSE 1.74%) all other models. Furthermore, detailed information behind models acquired, identifying most influencing factors as follows: temperature (56%), residence time (23%), heating rate (8%). partial dependence plot revealed how each factor affected target variable. Finally, easy-to-use software tool predicting built ANN-Rao-2 model. This study demonstrates huge potential machine learning presents in predictive modelling complex processes, reduces time-consuming expensive experimental work estimating yield.

Язык: Английский

Процитировано

90

Application of Artificial Intelligence in Combating High Antimicrobial Resistance Rates DOI Creative Commons
Ali A. Rabaan, Saad Alhumaid, Abbas Al Mutair

и другие.

Antibiotics, Год журнала: 2022, Номер 11(6), С. 784 - 784

Опубликована: Июнь 8, 2022

Artificial intelligence (AI) is a branch of science and engineering that focuses on the computational understanding intelligent behavior. Many human professions, including clinical diagnosis prognosis, are greatly useful from AI. Antimicrobial resistance (AMR) among most critical challenges facing Pakistan rest world. The rising incidence AMR has become significant issue, authorities must take measures to combat overuse incorrect use antibiotics in order rates. widespread practice not only resulted drug but also increased threat super-resistant bacteria emergence. As rises, clinicians find it more difficult treat many bacterial infections timely manner, therapy becomes prohibitively costly for patients. To rise rates, implement an institutional antibiotic stewardship program monitors correct use, controls antibiotics, generates antibiograms. Furthermore, these types tools may aid treatment patients event medical emergency which physician unable wait culture results. AI's applications healthcare might be unlimited, reducing time takes discover new antimicrobial drugs, improving diagnostic accuracy, lowering expenses at same time. majority suggested AI solutions meant supplement rather than replace doctor's prescription or opinion, serve as valuable tool making their work easier. When comes infectious diseases, potential game-changer battle against resistance. Finally, when selecting infections, data local programs ensuring treated quickly effectively. organizations such World Health Organization (WHO) have underlined necessity appropriate treating shortest feasible minimize spread resistant invasive strains.

Язык: Английский

Процитировано

88

Discovering topics and trends in the field of Artificial Intelligence: Using LDA topic modeling DOI
Dejian Yu, Bo Xiang

Expert Systems with Applications, Год журнала: 2023, Номер 225, С. 120114 - 120114

Опубликована: Апрель 13, 2023

Язык: Английский

Процитировано

74

Surveillance and response strategies for zoonotic diseases: a comprehensive review DOI Creative Commons
Manjeet Sharan, Deepthi Vijay, Jay Prakash Yadav

и другие.

Science in One Health, Год журнала: 2023, Номер 2, С. 100050 - 100050

Опубликована: Янв. 1, 2023

Out of all emerging infectious diseases, approximately 75% are zoonotic origin, with their source often traced back to animals. The emergence zoonoses is driven by a complex interplay between anthropogenic, genetic, ecological, socioeconomic, and climatic factors. This intricate web influences poses significant challenges for the prediction prevention outbreaks. Effective coordination collaboration among animal, human, environmental health sectors essential proactively addressing major diseases. Despite advancements in surveillance diagnostic practices, continues be pressing global concern. Therefore, prioritizing disease paramount importance as part comprehensive containment strategy. Furthermore, evaluating existing systems provides insights into faced, which can mitigated through implementation 'One Health' principles involving relevant stakeholders. To initiate multisectoral partnerships, it crucial identify priorities core themes equitable inputs from various sectors. Strengthening surveillance, promoting data sharing, enhancing laboratory testing capabilities, fostering joint outbreak responses both human animal will establish necessary infrastructure effectively prevent, predict, detect, respond threats, thereby reinforcing security. review assesses approaches offering an overview agencies engaged monitoring outlines components required at human-animal-environment interface designing networks. Additionally, discusses key steps executing effective One Health approach, while highlighting encountered establishing such robust system.

Язык: Английский

Процитировано

61

Application of artificial intelligence for resilient and sustainable healthcare system: systematic literature review and future research directions DOI
Laxmi Pandit Vishwakarma, Rajesh Kumar Singh, Ruchi Mishra

и другие.

International Journal of Production Research, Год журнала: 2023, Номер unknown, С. 1 - 23

Опубликована: Март 13, 2023

Recent years have witnessed increased pressure across the global healthcare system during COVID-19 pandemic. The pandemic shattered existing operations and taught us importance of a resilient sustainable system. Digitisation, specifically adoption Artificial Intelligence (AI) has positively contributed to developing in recent past. To understand how AI contributes building system, this study based on systematic literature review 89 articles extracted from Scopus Web Science databases is conducted. organised around several key themes such as applications, benefits, challenges using technology sector. It observed that wide applications radiology, surgery, medical, research, development Based analysis, research framework proposed an extended Antecedents, Practices, Outcomes (APO) framework. This comprises applications' antecedents, practices, outcomes for Consequently, three propositions are drawn study. Furthermore, our adopted theory, context methodology (TCM) provide future directions, which can be used reference point studies.

Язык: Английский

Процитировано

53

Lightweight deep CNN-based models for early detection of COVID-19 patients from chest X-ray images DOI Open Access
Haval I. Hussein,

Abdulhakeem O. Mohammed,

Masoud Muhammed Hassan

и другие.

Expert Systems with Applications, Год журнала: 2023, Номер 223, С. 119900 - 119900

Опубликована: Март 18, 2023

Язык: Английский

Процитировано

48