ArticleProbiotics and antimicrobial proteins2025
Uncovering the Probiotic Supplement Landscape: Market Offerings, Sales Patterns, and Future Forecasts Using Machine Learning Approach - A Case Study of Montenegro.
Article in Probiotics and antimicrobial proteins, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Genesis, Health Benefits, and Future Perspectives of Probiotics: Exploring Endogenous and Exogenous Classes, Innovations, and Research Gaps.Probiotics and antimicrobial proteins · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Global increasing awareness about the health benefits of probiotics resulted to explorational growth in probiotic food supplement market. However, in some countries such as Montenegro, specific probiotic supplement regulation and comprehensive market analysis are absent, hampering the understanding of consumer preferences, market trends, and potential economic impacts of this industry. This article aims to delve into the Montenegrin market of probiotic food supplements, thoroughly examining various product types and their key characteristics. Using the case study of a pharmacy chain, as an example of organizational level, the sales, sale patterns, and trends are examined. Furthermore, we developed and employed a machine learning model for forecasting future sales. The market analysis highlighted the importance of setting national probiotic supplement regulations to enhance Montenegrin consumer understanding and trust, ensuring product efficacy and safety. Our study clearly showed increased interest in probiotic supplements as well as a constant positive trend in probiotic supplement sales. Furthermore, we found the correlation between foreign tourist visits in Montenegro and the yearly seasonality of probiotic supplement sales. Developed support vector regression machine learning model on time series data showed a good forecasting accuracy, clearly indicating that the same could be used for national sales forecasting. The insights from this study could promote the establishment of national probiotic supplement regulations, enhancing consumer protection and market credibility. Additionally, developed machine learning model provides the industry with valuable predictive tool, enabling companies to optimize their supply chains, effectively meet demand, and make data-driven decisions that could support sustainable market growth.
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What Socratic holds
Registered trials
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 Socratic graph.