Evidence map›Paper›PMID 42791755›Full record

ReviewAnimals : an open access journal from MDPI2026

A Narrative Review of Early Pregnancy Diagnosis Technologies for Livestock: From Conventional to Intelligent Systems.

Yang Shen, Yujie Zhang, Junyi Meng, Yutong Han, Jitong Xu, Hongying Wang, Liangju Wang

Abstract readReview
In one paragraph

Review in Animals : an open access journal from MDPI, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

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

7 authors.

Yang ShenCollege of Engineering, China Agricultural University, Beijing 100083, China.
Yujie ZhangCollege of Engineering, China Agricultural University, Beijing 100083, China.
Junyi MengCollege of Engineering, China Agricultural University, Beijing 100083, China.ORCID 0009-0002-2818-1643
Yutong HanCollege of Engineering, China Agricultural University, Beijing 100083, China.
Jitong XuCollege of Engineering, China Agricultural University, Beijing 100083, China.ORCID 0009-0001-0451-1129
Hongying WangCollege of Engineering, China Agricultural University, Beijing 100083, China.
Liangju WangCollege of Engineering, China Agricultural University, Beijing 100083, China.ORCID 0000-0002-6936-6145

Funding

China Agriculture Research System 42
6 · The paper itself

Abstract

Accurate and efficient early pregnancy diagnosis (EPD) in livestock is crucial for optimizing breeding management and enhancing productivity in modern animal husbandry. Over the past century, EPD technology has evolved from empirical methods to sophisticated techniques, encompassing biochemical marker detection, ultrasonic imaging, and further extending to emerging non-invasive approaches such as infrared thermography (IRT) and spectroscopic analysis. These advancements have not only improved diagnostic accuracy but also broadened the research scope to include small livestock and multiple species. This review critically examines the historical evolution, current methodologies, and applications of EPD technology, with a focus on analyzing the advantages and limitations of both traditional and emerging techniques. Additionally, it explores the potential of multimodal fusion strategies and artificial intelligence (AI) in EPD. At present, machine vision, wearable monitoring, and several AI applications remain prospective approaches rather than validated tools for routine EPD. The conclusion highlights that, despite significant progress, current technologies still face limitations in achieving in situ, non-contact, and high-throughput detection. Looking ahead, the integration of cutting-edge technologies, such as AI, small wearable sensors, and physiological time-series data analysis, holds promise for overcoming these bottlenecks, enabling more intelligent and efficient pregnancy diagnosis, and providing scientific support for modern animal husbandry.

Indexed as

artificial intelligencebiomarkersearly pregnancy diagnosisimaging techniqueslivestockspectroscopy

Identifiers

PMID42791755
PMCPMC13603720

What OpenQuestion holds

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Read underepoch 390

Registered trials

None linked

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.