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Artificial intelligence and machine learning in precision medicine: A paradigm shift in big data analysis.

Mehar Sahu1, Rohan Gupta1, Rashmi K Ambasta1

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Area of Science:

  • Biomedical Informatics
  • Computational Biology
  • Healthcare Technology

Background:

  • Precision medicine tailors treatments to individual patient phenotypes, addressing unique responses to therapies.
  • Artificial intelligence (AI) offers advanced analytical capabilities crucial for deciphering complex biological data.
  • The convergence of AI and precision medicine is vital for overcoming current healthcare challenges.

Purpose of the Study:

  • To explore the multifaceted role of AI in advancing precision medicine.
  • To discuss the evolution and impact of AI on healthcare delivery.
  • To highlight the synergistic potential between AI and precision medicine.

Main Methods:

  • Review of current literature on AI applications in precision medicine.
  • Analysis of AI's role in identifying patient phenotypes and treatment responses.
  • Discussion of big data analytics and nanomaterial integration in AI-driven precision medicine.

Main Results:

  • AI is reshaping the landscape of precision medicine, enhancing diagnostic and therapeutic strategies.
  • Synergies between AI and precision medicine demonstrate significant promise for improved healthcare outcomes.
  • Big data analytics and nanomaterials are key components in advancing AI-powered precision medicine.

Conclusions:

  • AI integration is revolutionizing precision medicine, leading to more personalized and effective healthcare.
  • The continued evolution of AI in this field holds immense potential for future medical breakthroughs.
  • Addressing challenges and leveraging opportunities in AI for precision medicine is critical for advancing patient care.