Charting New Frontiers: AI, Machine Learning, and Deep Learning in Brain and Heart Health

Charting New Frontiers: AI, Machine Learning, and Deep Learning in Brain and Heart Health

Authors

  • Shehroz khan Glasgow Caledonian university, Email: SKHAN236@caledonian.ac.uk
  • Muhammad Bin Nazir Department of Computer Science, COMSATS University Islamabad Abbottabad Campus, Email: malik.awan630@gmail.com
  • Ibrar Hussain Department of Computer Science, University of Punjab, Email: 2021-pgcma-38@nca.edu.pk

Keywords:

AI, machine learning, deep learning, brain health, heart health

Abstract

The intersection of artificial intelligence (AI), machine learning (ML), and deep
learning (DL) has opened new frontiers in healthcare, particularly in the domains of brain and heart
health. This study explores the application of AI-driven approaches to improve diagnosis,
prognosis, and treatment strategies for neurological and cardiovascular diseases. Leveraging largescale datasets and advanced analytical techniques, including deep neural networks, the study aims
to elucidate the potential of cognitive computing in revolutionizing healthcare delivery and patient
outcomes. In the realm of brain health, AI-enabled imaging analysis holds promise for early
detection and characterization of neurological conditions such as Alzheimer's disease, Parkinson's
disease, and stroke. By leveraging complex patterns and spatial relationships in medical images,
deep learning algorithms can assist clinicians in accurate diagnosis and prediction of disease
progression. Moreover, AI-driven approaches enable personalized treatment planning and
intervention strategies tailored to individual patient profiles, ultimately leading to improved quality
of care and patient outcomes. Similarly, in the field of heart health, AI-powered predictive
modeling offers valuable insights into cardiovascular risk assessment, disease prevention, and
management. By integrating diverse sources of patient data, including electronic health records,
wearable devices, and genetic information, machine learning algorithms can identify high-risk
individuals and prioritize interventions aimed at reducing the burden of cardiovascular diseases.
Furthermore, AI-driven decision support systems empower clinicians with real-time insights and
evidence-based recommendations, facilitating more informed clinical decision-making and
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Volume 18 no. 2
Revista Española de Documentación Científica
eISSN: 1988-4621 pISSN: 0210-0614
improved patient management. The findings of this study underscore the transformative potential
of AI, ML, and DL in shaping the future of healthcare delivery, particularly in the domains of brain
and heart health. By harnessing the power of cognitive computing, healthcare providers can unlock
new avenues for precision medicine, personalized care, and population health management.
However, challenges related to data privacy, algorithm bias, and regulatory compliance must be
addressed to realize the full benefits of AI-driven healthcare solutions. Collaborative efforts
between researchers, clinicians, policymakers, and industry stakeholders are essential to overcome
these challenges and ensure the ethical and responsible deployment of AI technologies in
healthcare. In conclusion, this study highlights the pivotal role of AI, ML, and DL in charting new
frontiers in brain and heart health, offering unprecedented opportunities for innovation and
advancement in healthcare delivery and patient care.

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Published

2024-04-16

How to Cite

Shehroz khan, Muhammad Bin Nazir, & Ibrar Hussain. (2024). Charting New Frontiers: AI, Machine Learning, and Deep Learning in Brain and Heart Health. Revista Espanola De Documentacion Cientifica, 18(02), 209–237. Retrieved from http://redc.revistas-csic.com/index.php/Jorunal/article/view/214

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