Reacción a "Two AI models demonstrate their potential for patient management using simulations and real-world data"

Recent advances in medical AI indicate that the most sophisticated systems are now capable of achieving performance levels comparable to, and in some cases exceeding, those of physicians in specific clinical tasks such as diagnosis, test selection, treatment prescribing, and patient follow-up.

Two recent studies, focusing on the AMIE and MIRA systems, represent a significant qualitative leap compared with previous generations of medical AI. While AMIE stands out for its ability to conduct complex clinical conversations and manage patients across multiple consultations, MIRA takes this a step further by integrating directly into an electronic health record system and carrying out clinical actions such as ordering diagnostic tests, prescribing medications, and recommending hospital admissions.

The findings show that both systems were able to match or outperform physicians in simulated environments, particularly in areas such as adherence to clinical guidelines, the accuracy of recommendations, and medication safety.

However, the researchers themselves emphasise that these technologies are not yet ready for autonomous use in clinical practice. The studies were conducted in controlled settings using simulated patients, meaning that their effectiveness and safety must still be demonstrated in real-world hospitals and outpatient clinics.

Current evidence points towards a collaborative model in which healthcare professionals work alongside AI, rather than being replaced by it. In this scenario, AI would take on analytical, administrative, and decision-support tasks, while clinicians would remain responsible for clinical oversight, patient communication, managing uncertainty, and making final decisions regarding patient care.

These developments suggest that artificial intelligence could become a valuable ally in the coming years, helping to improve quality of care, reduce administrative burden, and support more consistent, evidence-based healthcare delivery, always under human supervision.

Neither AMIE nor MIRA is unique in this field. A recently published study in Science introduced an advanced AI model capable of outperforming physicians in diagnostic tasks within a controlled environment.

Taken together, these three studies represent three distinct generations of medical AI, and comparing them provides valuable insight into the direction in which the field is heading. If AMIE demonstrates that an AI system can interview patients like a physician, and the model reported in Science demonstrates that it can reason like a physician, MIRA seeks to demonstrate that it can work like a physician within the hospital environment. The most disruptive aspect of MIRA is not that it diagnoses conditions more effectively than other models, but that it translates clinical reasoning into structured clinical actions, such as ordering tests, prescribing treatments, scheduling procedures, and recommending admissions. From the perspective of healthcare system transformation, MIRA therefore represents what is arguably the closest step so far towards a truly integrated clinical co-pilot within hospital practice.

All three studies convey a common message: artificial intelligence is reaching performance levels that are comparable to, and in some cases exceed, those of many healthcare professionals in specific diagnostic and decision-making tasks. Nevertheless, the researchers stress that all current findings come from controlled or simulated environments, and that prospective studies involving real patients are still required to confirm safety, effectiveness, and impact on clinical outcomes.

Rather than suggesting the replacement of healthcare professionals, the authors view clinical support as the most promising role for these technologies. Under this model, AI would assume repetitive, administrative, and information-analysis tasks, while healthcare professionals would continue to be responsible for clinical oversight, final decision-making, and maintaining the human relationship at the heart of patient care.