In 1950, it took 50 years for medical knowledge to double; in 2020, only 73 days. A ZS survey of 1,000 doctors revealed that they were overwhelmed by the volume of patient data, stressing the importance of artificial intelligence (AI) to keep up with this pace. In France, AI is responding to the challenges of cancer, the main cause of death in men and the second most common in women, by offering more specific treatments and by reducing cases of overtreatment or undertreatment. AI makes it possible to personalize therapies, detect diseases earlier, and improve diagnostic accuracy. For example, in breast cancer, it analyzes mammograms 30 times faster and with almost 100% accuracy, minimizing the need for biopsies.
AI is making progress in disease prevention with its predictive capabilities. In 2022, researchers at Cedars Sinai developed an AI imaging tool that can detect pancreatic cancer up to three years earlier than a traditional diagnosis, potentially doubling the survival rate from 10% to 50%. In 2020, a deep-learning algorithm developed by Qure.ai improved the accuracy of early lung cancer diagnoses by 17% compared to conventional radiologies, in partnership with AstraZeneca to reduce mortality related to this disease on a global scale.
In Japan, SoftBank has partnered with Tempus, an American firm specializing in genomic analysis, to personalize cancer treatments based on patients' genetic profiles, using AI to optimize the effectiveness of care at scale. At the same time, in France, the start-up Spotlight Medical, a spin-off of the Institut Curie, is launching into precision medicine. Using advanced technologies developed by the Institut Curie, Les Mines de Paris — PSL and Inserm, Spotlight Medical aims to transform cancer treatment. By analyzing clinical data, the start-up is developing personalized treatments for all types of cancers, aimed at reducing side effects and improving survival rates, thus promising to significantly improve the quality of care.
Deploying AI in the medical sector poses significant challenges, especially when it comes to patient data privacy and algorithmic biases that can affect diagnoses and treatments. Rigorous regulatory frameworks are needed to ensure the ethical use of AI. In Japan, the integration of AI faces cultural and regulatory obstacles, with genomic tests* often limited to the failures of traditional treatments.
For the successful adoption of AI, ZS offers responsible, transparent, and competent implementation, by eliminating algorithmic biases and clarifying the capabilities of AI. SoftBank and Tempus ensure data anonymization, providing analytics at no cost to generate revenue. Close collaboration between engineers, technologists and health professionals is essential, as is continuing education in new technologies. In addition, healthcare institutions need to invest in research and development to stay at the forefront of innovation and maximize the benefits of AI.
AI is revolutionizing medicine by enabling more targeted and effective care, transforming the way diseases are diagnosed and treated. Faced with ethical and regulatory challenges, in-depth collaboration between health professionals and continuity in research are necessary to fully exploiting the potential of AI, while ensuring fair and secure use.
*A genome test is a procedure that analyzes an individual's DNA to identify specific genetic variations. This type of test provides a better understanding of a person's genetic heritage, including the risks of developing certain diseases, possible responses to medications, or hereditary characteristics.
Marie
AI consultant
marie.wald@strat37.com
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