Artificial intelligence (AI) is revolutionizing the field of healthcare, and more specifically the fight against cancer. By harnessing vast quantities of medical data, AI is making it possible to refine diagnoses, personalize treatments and significantly improve patients prognosis.
Complementary approaches for more accurate diagnosis
AI uses two main approaches to process information:
– The logical (or symbolic) approach: Inspired by human reasoning, this involves establishing precise rules to solve problems. In oncology, for example, an expert system could ask a doctor a series of questions and, by applying well-established medical rules, suggest a likely diagnosis.
– The digital (or data-driven) approach: Based on machine learning and deep learning, this involves training a system on large amounts of data. For example, to detect tumors in medical images, a deep learning algorithm learns to recognize the visual characteristics of a tumor and can then automatically detect new tumors.
Thanks to these approaches, AI makes it possible to :
– Detect cancers earlier: Deep learning algorithms analyze medical images with greater precision, enabling the detection of smaller lesions that are harder to identify by eye. These algorithms can also better differentiate between healthy and cancerous tissue.
– Personalize diagnoses: By combining information from genetic analyses, medical images and patient’s clinical data, AI can offer patients more precise and appropriate diagnoses.
Personalizing treatments using virtual twins
One of the most promising areas is that of virtual twins. These digital models, created from patient data, represent a virtual replica of the patient’s tumor. They can be used to :
– Simulate the effect of treatments: By testing different treatments on the virtual twin, doctors can choose the most effective therapy for each patient.
– Predict resistance to treatment: Virtual twins can help identify patients likely to develop resistance to treatments.
– Develop new therapies: They serve as a platform for testing new molecules and identifying new therapeutic targets.
The role of the doctor: a partnership with AI
AI is a powerful tool that complements the doctor’s expertise. It does not replace him, but helps him to make decisions. The doctor remains the guarantor of the patient’s overall care, interpreting the results provided by AI and monitoring the patient.
Challenges and prospects
The development of AI in oncology raises a number of challenges:
– Data quality: Biased data can lead to incorrect results.
– Data protection: Protecting patient privacy is essential.
– Explainability of algorithms: It’s important to understand how algorithms make their decisions so that they can evolve and improve .
https://www.inserm.fr/dossier/intelligence-artificielle-et-sante/
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