Evidence map›Paper›PMID 36618229›Full record

ArticleJournal of family medicine and primary care2022

Acceptance of artificial intelligence (AI)-based screening for breast health in urban slums of central Karnataka, India - SWOC analysis.

Shubha B Davalagi, Balu S Palicheralu, Sanjana S Narasimha Murthy, Shalini Hurlihal

Abstract read
In one paragraph

Article in Journal of family medicine and primary care, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Shubha B DavalagiDepartment of Community Medicine, JJM Medical College, Davangere, Karnataka, India.
Balu S PalicheraluDepartment of Community Medicine, JJM Medical College, Davangere, Karnataka, India.
Sanjana S Narasimha MurthyMedical Affairs, Eka Care, Orbi Health Pvt Ltd, Bangalore, Karnataka, India.
Shalini HurlihalDepartment of Community Medicine, JJM Medical College, Davangere, Karnataka, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Artificial intelligence-based imaging is a low-cost, radiation-free solution for the breast imaging process that uses infrared radiation emitted by the body. This is a novel procedure that, when feasible, could be a better solution, particularly in underprivileged communities having low access to breast health care. Aims: To assess the acceptance and explore challenges for an artificial intelligence-based screening solution for breast health among the urban slum population. Settings and Design: A mixed-method study was conducted in urban slums of central Karnataka, India. Material and Methods: The study was carried out for a period of two years in 2019-21 among women in the reproductive age group in urban slums of central Karnataka to understand the acceptance of an artificial intelligence-based imaging solution for screening breast health. In-depth interviews were conducted to identify the strength, weaknesses, opportunities, and challenges (SWOC) screening for breast health. Statistical Analysis Used: Quantitative data were analysed using Statistical Package for the Social Sciences (SPSS) v16.0, and for qualitative data, manual descriptive content analysis was carried out, and the sub-themes were generated. Results: A total of 768 women accessed the thermalytix ® breast imaging services, the majority of them in the age group 31-40 years (35%), belonging to the Muslim religion (68.5%) with a mean monthly family income of Rs. 11,950.67/- SWOC analysis identified reduced cost for the screening services and involvement of female self-help groups (SHGs) as strengths. Weaknesses included poor breast health awareness among women and the stigma associated with breast cancer. Conclusions: Artificial intelligence-based screening is a feasible solution for breast health in low-income, low health access areas like urban slums. Engagement of the local community and active involvement of the health system is of paramount importance for the sustainability of any novel strategy.

Indexed as

Acceptanceartificial intelligencebreasturban slum

Identifiers

PMID36618229
PMCPMC9810951

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.