Stakeholders of Cardiovascular Innovation Ecosystems in Germany DOI Open Access

С. Ю. Кириченко,

Adamantios Koumpis, Oya Beyan

et al.

International Journal of Online and Biomedical Engineering (iJOE), Journal Year: 2023, Volume and Issue: 19(18), P. 4 - 17

Published: Dec. 22, 2023

This paper aims to provide a first attempt towards analysis innovation ecosystems for cardiovascular pathologies in Germany through the use of stakeholder model. We present essential stakeholders development and deployment innovations field research medicine, primary functions they fulfill context these ecosystems. The adopted approach consists implementation multilevel system model analyzing this particular field. Data acquisition transpired systematic literature review multiple articles studies. phases were executed until reaching point at which considerable amount data was discovered, ensuring consistency across various sources. demonstrate that medicine involve interconnected networks different fields. Moreover, an investigation particularly Germany, we undertaken by each stakeholder, are participation findings presented hold potential bring better understanding pathology Germany. assertion is substantiated comprehensive examination relevant scientific literature.

Language: Английский

Redefining Healthcare DOI

Simanpreet Kaur,

Anjali

Advances in medical technologies and clinical practice book series, Journal Year: 2024, Volume and Issue: unknown, P. 157 - 177

Published: June 14, 2024

This chapter explores how artificial intelligence (AI) is revolutionising healthcare, with a focus on AI may improve operational effectiveness, individualised care, and diagnostic accuracy. It examines uses in personalised medicine, medical imaging analysis, predictive analytics, highlighting the profound shifts these technologies bring to provision of healthcare. Examined are ethical, privacy, regulatory issues, emphasising significance responsible balanced approach innovation. The also discusses lessen healthcare inequalities increase accessibility everywhere. In order guarantee maximises advantages while addressing social problems, it argues for collaborative approach, recommending continual research, multidisciplinary cooperation, strong ethical frameworks. Researchers, policymakers, practitioners who navigating changing terrain

Language: Английский

Citations

5
Growth hacking: Leveraging hyper-scalability, hyper-specialization, and human-centric strategies for competitive advantage DOI Creative Commons
Veronica Scuotto, Theofilos Tzanidis, Alan Murray

et al.

Journal of Business Research, Journal Year: 2025, Volume and Issue: 190, P. 115217 - 115217

Published: Feb. 7, 2025

Language: Английский

Citations

0
Mind the gap: unveiling the advantages and challenges of artificial intelligence in the healthcare ecosystem DOI

Simona Curiello,

Enrica Iannuzzi, Dirk Meissner

et al.

European Journal of Innovation Management, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 20, 2025

Purpose This work provides an overview of academic articles on the application artificial intelligence (AI) in healthcare. It delves into innovation process, encompassing a two-stage trajectory exploration and development followed by dissemination adoption. To illuminate transition from first to second stage, we use prospect theory (PT) offer insights effects risk uncertainty individual decision-making, which potentially lead partially irrational choices. The primary objective is discern whether clinical decision support systems (CDSSs) can serve as effective means “cognitive debiasing”, thus countering perceived risks. Design/methodology/approach study presents comprehensive systematic literature review (SLR) adoption We selected English dated 2013–2023 Scopus, Web Science PubMed, found using keywords such “Artificial Intelligence,” “Healthcare” “CDSS.” A bibliometric analysis was conducted evaluate productivity its impact this topic. Findings Of 322 articles, 113 met eligibility criteria. These pointed widespread reluctance among physicians adopt AI systems, primarily due trust-related issues. Although our underscores positive healthcare, it barely addresses associated Research limitations/implications has certain limitations, including potential concerns regarding generalizability, biases reliance theoretical frameworks that lack empirical evidence. Originality/value uniqueness lies examination healthcare professionals’ perceptions risks with implementing systems. Moreover, liability issues involving range stakeholders, algorithm developers, Internet Things (IoT) manufacturers, communication cybersecurity providers.

Language: Английский

Citations

0
Applications and Considerations of Artificial Intelligence in Veterinary Sciences: A Narrative Review DOI Creative Commons

Hesameddin Akbarein,

Mohammad Hussein Taaghi,

Mohammad Reza Mohebbi

et al.

Veterinary Medicine and Science, Journal Year: 2025, Volume and Issue: 11(3)

Published: April 2, 2025

In recent years, artificial intelligence (AI) has brought about a significant transformation in healthcare, streamlining manual tasks and allowing professionals to focus on critical responsibilities while AI handles complex procedures. This shift is not limited human healthcare; it extends veterinary medicine as well, where AI's predictive analytics diagnostic abilities are improving standards of animal care. Consequently, healthcare systems stand gain notable advantages, such enhanced accessibility, treatment efficacy, optimized resource allocation, owing the seamless integration AI. article presents comprehensive review manifold applications within domain science, categorizing them into four domains: clinical practice, biomedical research, public health, administration. It also examines primary machine learning algorithms used relevant studies, highlighting emerging trends field. The research serves valuable for scholars, offering insights current serving starting point those new

Language: Английский

Citations

0
Revolutionising healthcare with artificial intelligence: A bibliometric analysis of 40 years of progress in health systems DOI Creative Commons
Walayat Hussain, Mohamed A. Mabrok, Honghao Gao

et al.

Digital Health, Journal Year: 2024, Volume and Issue: 10

Published: Jan. 1, 2024

The development of artificial intelligence (AI) has revolutionised the medical system, empowering healthcare professionals to analyse complex nonlinear big data and identify hidden patterns, facilitating well-informed decisions. Over last decade, there been a notable trend research in AI, machine learning (ML), their associated algorithms health systems. These approaches have transformed enhancing efficiency, accuracy, personalised treatment, decision-making. Recognising importance growing topic area, this paper presents bibliometric analysis AI utilises Web Science (WoS) Core Collection database, considering documents published area for four decades. A total 64,063 papers were identified from 1983 2022. evaluates various perspectives, such as annual published, citations, highly cited papers, most productive institutions, countries. visualises relationship among scientific actors by presenting bibliographic coupling co-occurrences author's keywords. indicates that field began its significant growth late 1970s early 1980s, with since 2019. influential institutions are USA China. study also reveals community's top keywords include ‘ML’, ‘Deep Learning’, ‘Artificial Intelligence’.

Language: Английский

Citations

3
Gray Level Co-Occurrence Matrices and Support Vector Machine for Improved Lung Cancer Detection DOI Open Access
Mohtar Yunianto, Suparmi Suparmi, C. Cari

et al.

International Journal of Online and Biomedical Engineering (iJOE), Journal Year: 2023, Volume and Issue: 19(05), P. 129 - 145

Published: April 27, 2023

A detection system based on digital image processing and machine learning classification was developed to detect normal cancerous lung conditions. 340 data from LIDC –IDRI were processed through several stages. The first stage is pre-processing using three filter variations contrast stretching, which reduce noise increase contrast. segmentation process uses Otsu Thresholding clarify the ROI of image. texture feature extraction with GLCM applied 21 variations. Data used as a label value learned by in form SVM. results training are confusion matrix shows that high pass has higher accuracy than other two proposed method assessed terms accuracy, precision recall. model provided an 99.67 % 97.50 testing data.

Language: Английский

Citations

5
Integrative analysis of Text-to-Image AI systems in architectural design education: pedagogical innovations and creative design implications DOI Creative Commons
Nuno Montenegro

Journal of Architecture and Urbanism, Journal Year: 2024, Volume and Issue: 48(2), P. 109 - 124

Published: Oct. 11, 2024

This study explores the potential of Text-to-Image (T2I) AI systems in architectural design education, particularly during conceptual phase. Through a structured two-stage workshop, architecture students used T2I to conceptualize public building project, focusing on bird’s eye and interior perspectives. These AI-assisted designs were subsequently refined align with specific site conditions programmatic requirements. The reveals AI’s ability expand creative possibilities while highlighting its limitations biases. findings emphasize necessity for critical informed approach when integrating into education practice, addressing ethical considerations. Future research directions are proposed optimize applications design, address inherent biases systems, enhance discourse role shaping future practices.

Language: Английский

Citations

1
How Can Artificial Intelligence Transform the Future Design Paradigm and Its Innovative Competency Requisition: Opportunities and Challenges DOI
Yuqi Liu, Zhiyong Fu, Tiantian Li

et al.

Lecture notes in computer science, Journal Year: 2023, Volume and Issue: unknown, P. 131 - 148

Published: Jan. 1, 2023

Language: Английский

Citations

3
Artificial Intelligence-Based Chatbot to Support Public Health Services in Indonesia DOI Open Access
Rudi Setiawan, Rossi Iskandar,

Nadilla Madjid

et al.

International Journal of Interactive Mobile Technologies (iJIM), Journal Year: 2023, Volume and Issue: 17(19), P. 36 - 47

Published: Oct. 10, 2023

The aim of this study is to build an artificial intelligence chatbot application support public health services. acts as information service that can replace the role humans. analysis functional needs was obtained from submitted by one heads centers in Indonesia. This uses Scrum method with pregame stages produce a plan consisting and non-functional requirements conceptual design chatbot, which will be developed using Unified Modeling Language (UML) diagrams. process finding answers matching graph master technique, backtrack utilizes depth-first search strategy. There are 6 topics services, including schedules, information, registration, diseases, drugs, early care services for users. Tests conducted on these showed average correct answer ratio 93.1% out total 251 questions. result usability measurement has been built system scale value 80.1, indicating chatbots acceptable use.

Language: Английский

Citations

2
Identification of Medical Ecosystems in the Field of Mental Health and Cardiovascular Diseases at the Cologne Site DOI Open Access

Cara Dannenberg,

J. de P. Heimann,

Adamantios Koumpis

et al.

International Journal of Online and Biomedical Engineering (iJOE), Journal Year: 2024, Volume and Issue: 20(05), P. 66 - 77

Published: March 15, 2024

As part of the Europe-wide smart health innovation hub implemented in context Horizon Europe SHIFT-HUB project, our work concerns identification specific medical research ecosystems two fields, namely cardiovascular diseases and mental illness, with Cologne as central location. To achieve this aim, websites involved organizations were used for data purposes, members each respective ecosystem or network identified by acquiring information about their cooperation partners. A variety selection criteria have been applied to filter out whether these partners suitable be considered a further starting point research. The results indicate existence location, which various stakeholders, including healthcare institutions, providers, foundations, NGOs, business community, closely together. Larger institutions are usually networked at an international level, while smaller increasingly depend on foster regional partnerships. This promotes exchange knowledge level facilitates direct contact people affected, i.e., patients’ groups. Research both fields often receive financial support from commercial organizations, highlights importance community’s involvement exploiting promoting quality healthcare. article complexity interdisciplinarity particular ecosystems, all different categories comprising indispensable position. interaction amongst stakeholders international, regional, local levels can significantly help deploy resources more effectively improve life suffering any conditions.

Language: Английский

Citations

0