Precision Medicine: AI and Machine Learning Advancements in Neurological and Cardiac Health

Precision Medicine: AI and Machine Learning Advancements in Neurological and Cardiac Health


  • Ibrar Hussain Department of Computer Science, University of Punjab, Email:
  • Shehroz khan Glasgow Caledonian university, Email:
  • Muhammad Bin Nazir Department of Computer Science, COMSATS University Islamabad Abbottabad Campus, Email:


Precision Medicine, Artificial Intelligence, Machine Learning, Neurological Health, Cardiac Health


Precision medicine, propelled by advancements in artificial intelligence (AI) and
machine learning, is revolutionizing the diagnosis, treatment, and management of neurological and
cardiac health conditions. This paper explores the transformative potential of AI-driven
approaches in personalized healthcare delivery, focusing on their applications in neurological
disorders such as stroke, Alzheimer's disease, and epilepsy, as well as cardiac conditions including
coronary artery disease and heart failure. In neurological health, AI and machine learning
technologies offer unprecedented opportunities for early detection and accurate diagnosis of
conditions such as stroke. Deep learning algorithms trained on vast datasets of medical images and
clinical data can rapidly analyze neuroimaging studies and identify biomarkers indicative of
disease pathology. Furthermore, AI-driven predictive analytics models can assess individual risk
profiles and guide personalized treatment decisions, optimizing patient outcomes and resource
allocation in acute and chronic neurological conditions. Similarly, in cardiac health, AI-driven
approaches are reshaping the landscape of cardiovascular medicine, from risk assessment and
disease prediction to treatment selection and monitoring. Machine learning algorithms analyze
multimodal data streams, including electrocardiograms (ECGs), echocardiograms, and wearable
sensor data, to detect cardiac abnormalities, predict adverse events, and tailor interventions to
individual patient needs. By harnessing the power of big data and advanced analytics, precision
medicine strategies are paving the way for more targeted and effective therapies in cardiac care.
Key challenges in the implementation of AI-driven precision medicine include data privacy
concerns, regulatory hurdles, and the need for interdisciplinary collaboration between clinicians,
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eISSN: 1988-4621 pISSN: 0210-0614
data scientists, and policymakers. Addressing these challenges is essential to realizing the full
potential of AI and machine learning in transforming healthcare delivery and improving patient
outcomes. In conclusion, the integration of AI and machine learning technologies into precision
medicine approaches holds immense promise for advancing neurological and cardiac health. By
enabling more accurate diagnosis, personalized treatment strategies, and proactive disease
management, AI-driven precision medicine has the potential to revolutionize healthcare delivery
and improve the lives of patients with neurological and cardiac conditions.




How to Cite

Ibrar Hussain, Shehroz khan, & Muhammad Bin Nazir. (2024). Precision Medicine: AI and Machine Learning Advancements in Neurological and Cardiac Health. Revista Espanola De Documentacion Cientifica, 18(02), 150–179. Retrieved from