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Inferences of Funding in Research in Women's Health and Artificial Intelligence (AI) Dependability for Healthcare and FemTech Leaders.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	Inferences of Funding in Research in Women's Health and Artificial Intelligence (AI) Dependability for Healthcare and FemTech Leaders./
Author:	Mutilva, Sandra.
Description:	1 online resource (157 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 85-09, Section: B.
Contained By:	Dissertations Abstracts International85-09B.
Subject:	Psychology. -
Online resource:	click for full text (PQDT)
ISBN:	9798381959727

Inferences of Funding in Research in Women's Health and Artificial Intelligence (AI) Dependability for Healthcare and FemTech Leaders.
Mutilva, Sandra.

Inferences of Funding in Research in Women's Health and Artificial Intelligence (AI) Dependability for Healthcare and FemTech Leaders. - 1 online resource (157 pages)

Source: Dissertations Abstracts International, Volume: 85-09, Section: B.

Thesis (Ph.D.)--Adler University, 2023.

Includes bibliographical references

Artificial intelligence's (AI) transformative potential in healthcare's positive social change has been recognized in recent years; however, a research gap in women's health challenges reliable AI-driven innovations. Historical male-centric research skews healthcare understanding, leading to women receiving interventions based on such studies. This disparity, marked by women's underrepresentation and the trivialization of their health concerns, is perpetuated by research grant discrimination. The current study addressed these gaps through a thematic literature review, exploring AI and women's health for potential transformative outcomes within feminist and biomedical frameworks. The researcher conducted a survey of 82 global experts, including women's health specialists, AI professionals, researchers, regulatory authorities, FemTech entrepreneurs, and educators. The study tested the hypothesis (H01), asserting that, due to disparities in funding for women's health research, there is no statistical significance in the reliability of AI applications for women's health among FemTech and healthcare leaders. Contrary to the hypothesis, the results, utilizing frequencies, correlation, and regression analyses, supported H1, revealing a statistically significant correlation between funding disparities and perceived AI application reliability. The findings underscore the pressing need for public awareness regarding equity in women's health research, aiming to foster inclusivity in technology. This awareness is crucial for making informed decisions through gender-specific AI applications, guiding FemTech and healthcare leaders toward promoting a more equitable healthcare landscape.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2024

Mode of access: World Wide Web

ISBN: 9798381959727Subjects--Topical Terms:

555998
Psychology.
Subjects--Index Terms:

Healthcare leadersIndex Terms--Genre/Form:

554714
Electronic books.

Inferences of Funding in Research in Women's Health and Artificial Intelligence (AI) Dependability for Healthcare and FemTech Leaders.
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