Much of the global genius debate revolves around the ethical use of these technological advances. However, another edge to think about this issue is the real impact of health genius as a compassionate effect and effective access guarantee to new health paradigms.
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Life science companies are especially interested in launching patient -centered businesses, particularly those driven by artificial intelligence (AI). According to a BCG (2024) survey, 54% of pharmaceutical companies and Medical technology plan to launch business promoted by genia in the next five years.
Visualizing these advances and development axes is vital to see what these innovations for people’s health management mean.
A fundamental function of genia today in health is the ability to make decisions and create new content based on data that For a human mind they would be classified as unstructured or excessive.
This new decision -making process is revolutionizing the speed at which clinical studies are developed. Genia is allowing researchers teams to reach conclusions about the future of studies that even the human mind could not reach due to their “Limited” aggregation and projection capacity.
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This is not a smaller issue if one takes into account that during the 60 years prior to the massification of AI (2023) the number of medicines approved in the United States for every billion dollars spent on ID had been reduced by half every nine years (M. Hutson – Nature 2024). Genia has the potential to reverse the level of efficiency of clinical research to reach better health care parameters.
Additionally, basic AI also offers cost reduction benefits, but above all in diagnostic precision. According to María López, Managing Director & Partner of BCG’s health practice is estimated that artificial intelligence is transforming operational efficiency into medical care, automating around of 35% of the tasks of health workers.
How much water does a query make in AI?
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The organization of huge data volumes is allowing tasks such as the digitalization of electronic medical records (EHR), but even improve the accuracy of the diagnosis through the crossing of data with predictive models. For example, automatic learning models can analyze medical images, such as mammography, To detect cancer tumors early, reducing consultation costs and improving diagnosis efficiency.
Finally, we can conclude that the future of medical care is being promoted by AI and promises continuous advances that will improve patient care, expedite operations and reduce costs. Now, the way innovation is assimilated by health systems can end up being the great parallel challenge that these advances will face.
These human abilities to complement the development of genia also go through assimilation from public and regulatory power. Genia and innovation in general have the ability to improve people’s quality of life. The acceptance of these changes and the speed of adhesion of them is their countercase from the field of public policy.
María José Sánchez García
ABBVIE CLUSTER NORTH GENERAL MANAGER
