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An experiment often consists of more than a single step. In this case, measurements at each step give rise to uncertainty. Because the measurements occur in successive steps, the uncertainty in one step necessarily contributes to that in the subsequent step. As we perform statistical analysis on these types of experiments, we must learn to account for the propagation of uncertainty from one step to the next. The propagation of uncertainty depends on the type of arithmetic operation performed on...
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Scientific progress and clinical uncertainty.

Luigi Tavazzi1

  • 1Maria Cecilia Hospital, GVM Care & Research, Ravenna, Cotignola, Italy.

European Heart Journal Supplements : Journal of the European Society of Cardiology
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Summary

Precision Medicine integrates genetics and artificial intelligence (AI) to address challenges in genome sequencing and modification for treating genetic diseases. AI

Keywords:
Artificial intelligenceDeep learningGene-editingGenomeGenotypingMachine learning

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Area of Science:

  • Genetics and Artificial Intelligence
  • Computational Neuroscience

Background:

  • Precision Medicine advancements rely on rapid developments in genetics and artificial intelligence (AI).
  • Current challenges in genetics include population-wide genome sequencing complexity and the high-risk nature of genome modification for treating genetic diseases.
  • Artificial intelligence, a field combining neuroscience and computer science, offers powerful computational capabilities.

Purpose of the Study:

  • To explore the intersection of genetic advancements and artificial intelligence within the context of Precision Medicine.
  • To discuss the implications of large-scale genome sequencing and gene editing technologies.
  • To examine the potential role and impact of artificial intelligence on medical practices and the future of the medical profession.

Main Methods:

  • Review of current trends in genetic sequencing and genome modification.
  • Analysis of artificial intelligence applications in medicine, including diagnostics, prognostics, and drug discovery.
  • Discussion of the challenges and opportunities presented by integrating these technologies.

Main Results:

  • Genome sequencing requires specialized knowledge, and the medical community is currently unprepared for widespread implementation.
  • Genome modification offers potential for treating genetic diseases but involves delicate techniques with significant risks.
  • Artificial intelligence is increasingly applied across various medical fields, from image analysis to drug development.

Conclusions:

  • The integration of AI and advanced genetics presents both opportunities and challenges for Precision Medicine.
  • The evolving landscape necessitates adaptation and training within the medical profession to leverage these powerful tools.
  • The future role of physicians will likely be redefined by the capabilities of AI and genetic technologies.