As more AI-driven healthcare products are brought to market, how can regulators keep pace with this rapidly evolving technology?
Artificial intelligence (AI) is becoming a force to be reckoned with in healthcare. Over the last decade or so, AI-based healthcare products have moved out of the proof-of-concept stage and have begun to rewrite our understanding of what might be possible.
To cite just a few examples: deep learning techniques have been used in dermatology to diagnose skin cancer, and in radiology to make better sense of CT scans. Surgeons are using robots integrated with AI, while pharma companies are using convolutional neural networks to identify promising drug candidates.
AI-based wearable devices are routinely used to monitor patients, flagging up any changes to their vital signs. There are even AI-based triage tools for Covid-19, which can determine who needs a PCR test.
Cybersécurité et PME : les risques à ne pas sous-estimer On pense souvent que seules…
Comment reconnaître une attaque de phishing et s’en protéger Le phishing ou « hameçonnage »…
Qu’est-ce que la cybersécurité ? Définition, enjeux et bonnes pratiques en 2025 La cybersécurité est…
Cybersécurité : les établissements de santé renforcent leur défense grâce aux exercices de crise Face…
L'IA : opportunité ou menace ? Les DSI de la finance s'interrogent Alors que l'intelligence…
Sécurité des identités : un pilier essentiel pour la conformité au règlement DORA dans le…
This website uses cookies.