AI Medical Compendium Topic

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Parturition

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Road Transport of Late-Pregnant Mares Advances the Onset of Foaling.

Journal of equine veterinary science
Cortisol is involved in the initiation of parturition and we hypothesized that increased maternal cortisol release advances the onset of foaling. Transport is a stressor for horses and induces an increase in cortisol release. To determine stress effe...

Technical note: Calving prediction in dairy cattle based on continuous measurements of ventral tail base skin temperature using supervised machine learning.

Journal of dairy science
In this study, we developed a calving prediction model based on continuous measurements of ventral tail base skin temperature (ST) with supervised machine learning and evaluated the predictive ability of the model in 2 dairy farms with distinct cattl...

Reliable Prediction Models Based on Enriched Data for Identifying the Mode of Childbirth by Using Machine Learning Methods: Development Study.

Journal of medical Internet research
BACKGROUND: The use of artificial intelligence has revolutionized every area of life such as business and trade, social and electronic media, education and learning, manufacturing industries, medicine and sciences, and every other sector. The new ref...

Transporting an Artificial Intelligence Model to Predict Emergency Cesarean Delivery: Overcoming Challenges Posed by Interfacility Variation.

Journal of medical Internet research
Research using artificial intelligence (AI) in medicine is expected to significantly influence the practice of medicine and the delivery of health care in the near future. However, for successful deployment, the results must be transported across hea...

Machine learning to predict pregnancy outcomes: a systematic review, synthesizing framework and future research agenda.

BMC pregnancy and childbirth
Machine Learning (ML) has been widely used in predicting the mode of childbirth and assessing the potential maternal risks during pregnancy. The primary aim of this review study is to explore current research and development perspectives that utilize...

Predicting preterm births from electrohysterogram recordings via deep learning.

PloS one
About one in ten babies is born preterm, i.e., before completing 37 weeks of gestation, which can result in permanent neurologic deficit and is a leading cause of child mortality. Although imminent preterm labor can be detected, predicting preterm bi...

Predictive analysis on the factors associated with birth Outcomes: A machine learning perspective.

International journal of medical informatics
BACKGROUND: Recent studies reveal that around 1.9 million stillbirths occur annually worldwide, with Sub-Saharan Africa having among the highest cases. Some Sub-Saharan African countries, including Ghana, failed to meet Millennium Development Goal 5 ...

Machine learning approach to investigate pregnancy and childbirth risk factors of sleep problems in early adolescence: Evidence from two cohort studies.

Computer methods and programs in biomedicine
BACKGROUND: This study aimed to predict early adolescent sleep problems using pregnancy and childbirth risk factors through machine learning algorithms, and to evaluate model performance internally and externally.

Advancing newborn care: Precise time of birth detection using ai-driven thermal imaging with adaptive normalization.

Computers in biology and medicine
Around 5%-10% of newborns need assistance to start breathing. Currently, there is a lack of evidence-based research, objective data collection, and opportunities for learning from real newborn resuscitation emergency events. Generating and evaluating...

Machine learning analysis of the relationships between traumatic childbirth experience with positive and negative fertility motivations in Iran in a community-based sample.

Reproductive health
BACKGROUND: Psychologically traumatic childbirth leads to short and long-term negative impacts on a woman's health and impacts future reproductive decisions. Considering the importance of fertility growth and strengthening positive fertility motivati...