A Synthesis of the Causes of ICT4D Projects’ Pilotitis: Prioritising the Remedies for the SDG2030 Agenda DOI
Tania Prinsloo, Funmi Adebesin

IFIP advances in information and communication technology, Journal Year: 2023, Volume and Issue: unknown, P. 63 - 77

Published: Jan. 1, 2023

Language: Английский

Challenges and strategies for wide-scale artificial intelligence (AI) deployment in healthcare practices: A perspective for healthcare organizations DOI
Pouyan Esmaeilzadeh

Artificial Intelligence in Medicine, Journal Year: 2024, Volume and Issue: 151, P. 102861 - 102861

Published: March 30, 2024

Language: Английский

Citations

73

Artificial Intelligence in Clinical Oncology: From Data to Digital Pathology and Treatment DOI Open Access
Kirthika Senthil Kumar, Vanja Mišković, Agata Blasiak

et al.

American Society of Clinical Oncology Educational Book, Journal Year: 2023, Volume and Issue: 43

Published: May 1, 2023

Recently, a wide spectrum of artificial intelligence (AI)–based applications in the broader categories digital pathology, biomarker development, and treatment have been explored. In domain these included novel analytical strategies for realizing new information derived from standard histology to guide selection development predict response. therapeutics, AI-driven drug target discovery, design repurposing, combination regimen optimization, modulated dosing, beyond. Given continued advances that are emerging, it is important develop workflows seamlessly combine various segments AI innovation comprehensively augment diagnostic interventional arsenal clinical oncology community. To overcome challenges remain with regard ideation, validation, deployment oncology, recommendations toward bringing this workflow fruition also provided clinical, engineering, implementation, health care economics considerations. Ultimately, work proposes frameworks can potentially integrate domains sustainable adoption practice-changing by community drive improved patient outcomes.

Language: Английский

Citations

35

The Effect of the COVID-19 Pandemic on Digital Health–Seeking Behavior: Big Data Interrupted Time-Series Analysis of Google Trends DOI Creative Commons
Robin van Kessel, Ilias Kyriopoulos, Brian Li Han Wong

et al.

Journal of Medical Internet Research, Journal Year: 2023, Volume and Issue: 25, P. e42401 - e42401

Published: Jan. 5, 2023

Background Due to the emergency responses early in COVID-19 pandemic, use of digital health care increased abruptly. However, it remains unclear whether this introduction was sustained long term, especially with patients being able decide between and traditional services once latter regained their functionality throughout pandemic. Objective We aim understand how public interest changed as proxy for health–seeking behavior what extent change sustainable over time. Methods used an interrupted time-series analysis Google Trends data break points on March 11, 2020 (declaration a pandemic by World Health Organization), December 20, (the announcement first vaccines). Nationally representative from February 2019 August 2021 were extracted 6 countries English dominant language: Canada, United States, Kingdom, New Zealand, Australia, Ireland. measured changes relative search volumes keywords online doctor, telehealth, health, telemedicine, app. In doing so, we capture prepandemic trend, immediate due gradual after announcement. Results Digital immediately all under study There some variation per country. searches declined spike, sometimes reverting levels. The vaccines did not consistently impact study. exception is volume app, which observed either stable or gradually increasing during Conclusions Our findings suggest that associated sustain, alluding remaining structural barriers. Further building capacity developing robust governance frameworks remain crucial facilitating transformation.

Language: Английский

Citations

32

Public Understanding and Expectations of Digital Health Evidence Generation: Focus Group Study DOI Creative Commons
Paulina Bondaronek, Jingfeng Li, Henry Potts

et al.

JMIR Formative Research, Journal Year: 2025, Volume and Issue: 9, P. e56523 - e56523

Published: Jan. 20, 2025

Abstract Background The rapid proliferation of health apps has not been matched by a comparable growth in scientific evaluations their effectiveness, particularly for available to the public. This gap prompted ongoing debate about types evidence necessary validate apps, especially as perceived risk level varies from wellness tools diagnostic aids. perspectives general public, who are direct stakeholders, notably underrepresented discussions on digital generation. Objective study aimed explore public understanding and expectations regarding required demonstrate apps’ including at varying levels risk. Methods A total 4 focus group were held with UK residents aged 18 years older, recruited through targeted advertisements ensure demographic diversity. Participants discussed views requirements 5 hypothetical ranging low-risk high-risk tools. Focus groups moderated using structured guide, data analyzed reflexive thematic analysis extract common themes. Results key themes established: personal needs, app functionality, social approval, testing, authority. relied experiences endorsements when judging effectiveness interventions, while making minimal reference traditional evidence. However, an increased, there was noticeable shift toward preferring authoritative sources, such government or National Health Service endorsements. Conclusions have preference that resonates level, but also show heightened demand guidance potential interventions increases. These should guide developers, regulators, policy makers they balance how achieve innovation, safety, trust landscape. Engaging evidence-generation processes ensuring transparency functionality testing can bridge between regulatory standards, fostering technologies.

Language: Английский

Citations

1

Holding AI to Account: Challenges for the Delivery of Trustworthy AI in Healthcare DOI Open Access
Rob Procter, Peter Tolmie, Mark Rouncefield

et al.

ACM Transactions on Computer-Human Interaction, Journal Year: 2022, Volume and Issue: 30(2), P. 1 - 34

Published: Dec. 22, 2022

The need for AI systems to provide explanations their behaviour is now widely recognised as key adoption. In this article, we examine the problem of trustworthy and explore what delivering means in practice, with a focus on healthcare applications. Work area typically treats Human–Computer Interaction involving individual user an system. However, argue here that overlooks important part played by organisational accountability how people reason about trust socio-technical settings. To illustrate importance accountability, present findings from ethnographic studies breast cancer screening treatment planning multidisciplinary team meetings show participants made themselves accountable both each other organisations which they are members. We use these enrich existing understandings requirements outline some candidate solutions problems making users organisationally. conclude outlining implications future work development AI, including ways our proposed may be re-used different application

Language: Английский

Citations

30

Physicians’ Perspectives on AI in Clinical Decision Support Systems: Interview Study of the CURATE.AI Personalized Dose Optimization Platform DOI Creative Commons
Smrithi Vijayakumar, V Vien Lee, Qiao Ying Leong

et al.

JMIR Human Factors, Journal Year: 2023, Volume and Issue: 10, P. e48476 - e48476

Published: Sept. 10, 2023

Background Physicians play a key role in integrating new clinical technology into care practices through user feedback and growth propositions to developers of the technology. As physicians are stakeholders involved iteration process, understanding their roles as users can provide nuanced insights workings these technologies that being explored. Therefore, physicians’ perceptions be critical toward validation, implementation, downstream adoption. Given increasing prevalence decision support systems (CDSSs), there remains need gain an in-depth expectations implementation. This paper explores CURATE.AI, novel artificial intelligence (AI)–based stage personalized dosing CDSSs, practice. Objective study aims understand perspectives CURATE.AI for work gather on considerations implementation AI-based CDSS tools. Methods A total 12 participants completed semistructured interviews examining knowledge, experience, attitudes, risks, future course combination therapy platform, CURATE.AI. Interviews were audio recorded, transcribed verbatim, coded manually. The data thematically analyzed. Results Overall, 3 broad themes 9 subthemes identified thematic analysis. covered perceived significant across various stages development, including trial, mass Conclusions laid out ways interpreted CDSS, research pointed during different exploration layered with relevant researchers.

Language: Английский

Citations

11

Lessons in complexity learned during a Canadian virtual pragmatic trial for prostate cancer survivorship DOI Creative Commons
Kaylen J. Pfisterer, Karen Young, Raima Lohani

et al.

Cancer Survivorship Research & Care, Journal Year: 2025, Volume and Issue: 3(1)

Published: March 14, 2025

Language: Английский

Citations

0

Personalized dose selection for the first Waldenström macroglobulinemia patient on the PRECISE CURATE.AI trial DOI Creative Commons
Agata Blasiak, Lester W. J. Tan, Li Ming Chong

et al.

npj Digital Medicine, Journal Year: 2024, Volume and Issue: 7(1)

Published: Aug. 27, 2024

Abstract The digital revolution in healthcare, amplified by the COVID-19 pandemic and artificial intelligence (AI) advances, has led to a surge development of technologies. However, integrating health solutions, especially AI-based ones, rare diseases like Waldenström macroglobulinemia (WM) remains challenging due limited data, among other factors. CURATE.AI, clinical decision support system, offers an alternative big data approaches calibrating individual treatment profiles based on that individual’s alone. We present case study from PRECISE CURATE.AI trial with WM patient, where, over two years, provided dynamic Ibrutinib dose recommendations clinicians (users) aimed at achieving optimal IgM levels. An 80-year-old male newly diagnosed requiring anemia was recruited for CURATE.AI-based dosing Bruton tyrosine kinase inhibitor Ibrutinib. primary secondary outcome measures were focused scientific logistical feasibility. Preliminary results underscore platform’s potential enhancing user patient engagement, addition efficacy. Based two-year-long enrollment into CURATE.AI-augmented treatment, this showcases how AI-enabled tools can management diseases, emphasizing integration AI enhance personalized therapy.

Language: Английский

Citations

3

Advancing laryngology through artificial intelligence: a comprehensive review of implementation frameworks and strategies DOI

Rachel B. Kutler,

Liang He,

Ross W. Green

et al.

Current Opinion in Otolaryngology & Head & Neck Surgery, Journal Year: 2025, Volume and Issue: unknown

Published: March 4, 2025

This review aims to explore the integration of artificial intelligence (AI) in laryngology, with specific focus on barriers preventing translation from pilot studies into routine clinical practice and strategies for successful implementation. Laryngology has seen an increasing number proof-of-concept demonstrating AI's ability enhance diagnostics, treatment planning, patient outcomes. Despite these advancements, few tools have been successfully adopted settings. Effective implementation requires application established science frameworks early design phase. Additional factors required AI applications include addressing needs, fostering diverse interdisciplinary teams, ensuring scalability without compromising model performance. Governance, epistemic, ethical considerations must also be continuously incorporated throughout project lifecycle ensure safe, responsible, equitable use technologies. While hold significant promise advancing its remains limited. Achieving meaningful will require a shift toward practical solutions that prioritize clinicians' patients' usability, sustainability, alignment workflows.

Language: Английский

Citations

0

Dissecting reality: navigating the implementation gap of AI in the NHS DOI Open Access
Ajay Aggarwal, Hutan Ashrafian

Bulletin of The Royal College of Surgeons of England, Journal Year: 2025, Volume and Issue: 107(3), P. 128 - 131

Published: May 1, 2025

Why do promising medical innovations struggle to gain traction in the NHS and how can organisations foster confidence, alignment adoption?

Language: Английский

Citations

0