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INNOSC Theranostics and
Pharmacological Sciences Biomarkers for early heart risks in pre-eclampsia

become more useful in the future as biosensor technology imaging-based AL algorithms further enable predictive
and digital health integration advance, guaranteeing modeling, improving early detection and personalized
prompt, precise, and easily accessible diagnostics for management strategies. Collectively, these advanced
maternal healthcare. imaging techniques offer a non-invasive, reproducible,
and highly sensitive approach for identifying CV risks in
7.2. AI and ML pre-eclampsia, significantly improving maternal and fetal
With their potential for early detection and risk assessment outcomes.
of CV problems linked to pre-eclampsia, AI and ML have
become revolutionary tools in the healthcare industry. 7.4. Wearable health technology
For prompt intervention, CV risks must be identified In the early detection of CV health problems, wearable
early. Large and complex datasets, such as biochemical, health technology has become a game-changer, especially
genetic, proteomic, clinical biomarker, and imaging data, in circumstances, such as pre-eclampsia. These cutting-
can be analyzed with algorithms driven by AI and ML edge tools make it easier to continuously monitor
to predict the development and course of pre-eclampsia. physiological indicators and provide real-time data that
Furthermore, integrating wearable health monitoring helps identify risk biomarkers. Wearable sensors have been
technology with AI-powered platforms improves the shown to be useful in monitoring heart rate variability
monitoring of blood pressure and heart rate variability and blood pressure. Furthermore, improvements in
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in real-time, resulting in a personalized risk profile. AI non-invasive biosensors have made it possible to assess
models that take into account biomarker levels, blood circulating biomarkers, such as sFlt-1 and PlGF, improving
pressure trends, and maternal history have shown superior predictive powers.
predicted accuracy. In addition, ML models, such as
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random forests and support vector machines have shown ML algorithms have been incorporated into smart
excellent accuracy in predicting hypertensive disorders wearable devices, such as smartwatches and patches,
during pregnancy by analyzing patient history and to forecast the course of diseases and send out tailored
physiological data. These tools outperform traditional notifications. A recent analysis showed that by identifying
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statistical methods by detecting non-linear patterns and minute hemodynamic changes weeks before clinical
interactions between variables. AI and ML developments symptoms, wearable devices could enhance early diagnosis
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have the potential to revolutionize pre-eclampsia care and treatment results. This demonstrates how wearable
by enabling the early detection of CV risks, enhancing technology may help prevent long-term CV problems
maternal-fetal outcomes, and reducing medical expenses. by changing the management of pre-eclampsia from
reactive to proactive. When paired with developments in
7.3. Advanced imaging techniques biomarker research, these technologies constitute a major
Cutting-edge imaging methods have become essential for breakthrough in the treatment of problems related to
the early detection and risk assessment of CV problems maternal and fetal health.
in pre-eclampsia. In patients with pre-eclampsia, early 8. Conclusion
indicators of CV dysfunction are detectable using
methods including echocardiography (ECG) and cardiac A paradigm change in maternal healthcare is provided
magnetic resonance imaging (MRI). For example, Doppler by the early detection of CV health risks in pre-eclampsia
ultrasound is frequently used to evaluate anomalies in through the development of biomarkers and creative tools,
uteroplacental blood flow, which are early markers of which also present new chances for risk prediction and
pre-eclampsia and its development into CV disorders. appropriate risk management. Combining these indicators
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In addition, high-resolution insights into the placental with cutting-edge diagnostic technologies, such as
function and structural alterations linked to pre-eclampsia wearable technology and ML algorithms, has the potential
have been demonstrated using MRI. Furthermore, a to completely transform personalized medicine methods
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thorough assessment of the hemodynamic changes and in CV and maternal-fetal health. To ensure prompt and
cardiac remodeling in afflicted patients is made possible by efficient therapy of pre-eclampsia and associated CV after-
three-dimensional ECG. effects, translational efforts are crucial in bridging the gap
between research and clinical practice.
Recent advancements, such as the integration of
computed tomography angiography for vascular imaging, The integration of multi-biomarker panels, advanced
have enhanced the precision of identifying endothelial diagnostic tools, and AI-driven technologies holds
dysfunction and vascular stiffness, which are both promise for revolutionizing the management of pre-
critical biomarkers of long-term CV risks. Innovations in eclampsia. Further research is required to: (i) validate

Volume 8 Issue 3 (2025) 98 doi: 10.36922/itps.7839