Dataset Information

Revolutionizing hysteroscopy outcomes: AI-powered uterine myoma diagnosis algorithm shortens operation time and reduces blood loss.

ABSTRACT:

Background

The application of artificial intelligence (AI) powered algorithm in clinical decision-making is globally popular among clinicians and medical scientists. In this research endeavor, we harnessed the capabilities of AI to enhance the precision of hysteroscopic myomectomy procedures.

Methods

Our multidisciplinary team developed a comprehensive suite of algorithms, rooted in deep learning technology, addressing myomas segmentation tasks. We assembled a cohort comprising 56 patients diagnosed with submucosal myomas, each of whom underwent magnetic resonance imaging (MRI) examinations. Subsequently, half of the participants were randomly designated to undergo AI-augmented procedures. Our AI system exhibited remarkable proficiency in elucidating the precise spatial localization of submucosal myomas.

Results

The results of our study showcased a statistically significant reduction in both operative duration (41.32 ± 17.83 minutes vs. 32.11 ± 11.86 minutes, p=0.03) and intraoperative blood loss (10.00 (6.25-15.00) ml vs. 10.00 (5.00-15.00) ml, p=0.04) in procedures assisted by AI.

Conclusion

This work stands as a pioneering achievement, marking the inaugural deployment of an AI-powered diagnostic model in the domain of hysteroscopic surgery. Consequently, our findings substantiate the potential of AI-driven interventions within the field of gynecological surgery.

SUBMITTER: Chen M

PROVIDER: S-EPMC10739391 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

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Publications

Revolutionizing hysteroscopy outcomes: AI-powered uterine myoma diagnosis algorithm shortens operation time and reduces blood loss.

Chen Minghuang M Kong Weiya W Li Bin B Tian Zongmei Z Yin Cong C Zhang Meng M Pan Haixia H Bai Wenpei W

Frontiers in oncology 20231208

<h4>Background</h4>The application of artificial intelligence (AI) powered algorithm in clinical decision-making is globally popular among clinicians and medical scientists. In this research endeavor, we harnessed the capabilities of AI to enhance the precision of hysteroscopic myomectomy procedures.<h4>Methods</h4>Our multidisciplinary team developed a comprehensive suite of algorithms, rooted in deep learning technology, addressing myomas segmentation tasks. We assembled a cohort comprising 56 ...[more]

PMID: 38144535

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Project description:BackgroundThe published data about alcohol consumption and uterine myoma are scanty and controversial: some studies found positive association whereas other studies showed no association.ObjectivesTo conduct a systematic review and meta-analysis to determine whether alcohol is a risk factor for myoma.Search strategyA MEDLINE/EMBASE search was carried out, supplemented by manual searches of bibliographies of the selected studies.Selection criteriaArticles published as full-length papers in English. In the review we included all identified studies. Otherwise, the inclusion criteria for studies included in the meta-analysis were: a) case-control or cohort studies, reporting original data; b) studies reporting original data on the association between alcohol consumption and myoma; c) diagnosis of myoma was ultrasound or histological confirmed and/or clinically based.Data collection and analysisA total of 6 studies were identified for the review and 5 studies were included in the meta-analysis. The primary outcome was the incidence of uterine myoma in ever versus never alcohol drinkers and when data were available, we also analyzed categories of alcohol intake. We assessed the outcomes in the overall population and then we performed a subgroup analysis according to study design. Pooled estimates of the odds ratios (OR) with 95% confidence interval (CI) were calculated using random effects models.Main resultsThe summary OR (95%CI) of myoma forever versus never alcohol intake was 1.12 (0.94-1.34) with significant heterogeneity. The summary OR for current versus never drinking was 1.33 (1.01-1.76) with no heterogeneity.ConclusionsEver alcohol consumption is not associated with myoma risk. Based on the data of two studies, current alcohol drinkers had a slightly borderline increased risk of diagnosis of myoma. In consideration of the very limited number of studies and the suggestion of a potential increased risk among current drinkers, further studies are required.

Dataset Information

Revolutionizing hysteroscopy outcomes: AI-powered uterine myoma diagnosis algorithm shortens operation time and reduces blood loss.

Background

Methods

Results

Conclusion

Publications

Revolutionizing hysteroscopy outcomes: AI-powered uterine myoma diagnosis algorithm shortens operation time and reduces blood loss.

Similar Datasets

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