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Researchers developed a model to predict newborn birth weight using routine pregnancy scans.
The project involved researchers from the Institute of Mathematical Sciences, Seethapathy Clinic and Hospital, Chennai and IISER Pune.
The model can reduce reliance on late-term ultrasounds, making birth weight prediction more accessible.
Researchers applied the Gompertz model to predict birth weight by analyzing data from routine scans of pregnant women
Gompertz model
Developed in the 19th century by mathematician Benjamin Gompertz
It was originally designed to model population growth in a constrained environment, such as a specific geographic region.
The model uses an S-shaped (sigmoid) curve to represent growth patterns that start slowly, accelerate, and then slow again as they approach a plateau.
Applications:
Biology: The Gompertz Model is used to study tumor growth and cell population dynamics, reflecting constrained growth in biological systems.
Epidemiology: Applied in predicting the spread of infectious diseases like COVID-19, capturing how transmission rates slow with interventions.
Ecology: Useful for modelling species population growth in habitats with limited resources, aiding conservation and ecosystem management.
Healthcare: To predict foetal birth weight, helping identify potential risks associated with low or high birth weight.
Aging Research: Employed to analyze mortality rates and lifespan patterns, contributing to studies on aging and longevity.
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