about AI and Medicine
AI and Medicine emerges from the convergence of scientific training, university teaching, learning, clinical reasoning and critical analysis of the real impact of artificial intelligence in health care.
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Biomedical scientist, MSc in Neuroimmunology, PhD in Physiology, Neurosciences professor at UFF and fifth-year medical student.
My work combines cognition, education, clinical reasoning and critical analysis of the impact of artificial intelligence on health care.
More than commenting on technology, the point is to translate real implications: what AI changes in medical education, clinical practice, communication with patients and institutional decisions.
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Learning and practice without shortcuts: less hype, more method; fewer vague promises, more responsible evidence-based application.
That translates into critical analysis, technical curation, educational product design and training applied to professionals and institutions that need to use AI in a consistent, ethical and clinically useful way.
The goal is not to replace professional thinking, but to qualify its application in real context, including knowing when to use AI and when not to use it.
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Our patients are not products. Technology in health care must answer to context, safety, clinical judgment and responsibility.
Patients are not exam questions. Learning, teaching and implementing AI require rigor, prudence and commitment to real-world application.