Management and systemic riskFrom pride to systemic risk
When an organization normalizes chronic exhaustion, it stops managing people and starts managing risk without recognizing it.
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Nexus Humanum texts for thinking about artificial intelligence from concrete healthcare practice.
Management and systemic riskWhen an organization normalizes chronic exhaustion, it stops managing people and starts managing risk without recognizing it.
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Foundational articleA reflection on technology, clinical practice, fragmented records, and human responsibility in non-ideal healthcare contexts.
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Clinical practiceHow to use generative AI to organize healthcare documentation quickly, with strict anonymization and human review.
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Healthcare management and AIHow AI can reduce bureaucratic overload and return judgment, care, and clinical time to healthcare workers.
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Nexus Simplex ClassroomA reading for nurses and technicians on how AI can relieve repetitive administrative and documentation tasks without replacing human expertise.
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Nexus Simplex ClassroomA reading for admissions, secretarial, billing, and healthcare management teams about AI applied to spreadsheets, forms, authorizations, schedules, and repetitive processes.
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Workforce careAn essay on retirement, professional identity, and the loneliness that is often absent from healthcare planning.
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Clinical cultureA reading on normalized fatigue, professional pride, and organizational risk in medicine.
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Patient safetyWhat the Vanderbilt case teaches about technology, automation, system stress, and clinical responsibility.
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Ethics and AIPractical principles for using artificial intelligence in medicine without losing humanity, equity, or responsibility.
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5P medicineDigital twins, personalized medicine, and concrete implementation challenges in Uruguay.
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5P medicineA clinical introduction to digital twins and predictive, preventive, personalized, participatory, and population medicine.
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History of AIPart one of a series on the idea of artificial intelligence before silicon.
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History of AIHow thinking became a formal problem before becoming computation.
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History of AIBabbage, Ada Lovelace, Turing, and the machine as an intellectual problem.
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History of AIData, statistics, and the birth of machine learning.
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History of AIThe leap toward deep learning and foundation models.
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Emergency care and AIWhen AI can help in emergency care and when it adds noise, risk, or false security.
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Clinical practice and AIWhy AI will not replace the physician, but may profoundly change medical practice.
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Healthcare divideHow AI can widen inequalities if it arrives without infrastructure, data, or governance.
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Clinical judgmentAutomation bias and the risk of confusing a screen with a clinical decision.
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Future of medicineAn open question for a time when information is no longer the scarce resource.
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Health systemsWhat happens when pressure stops being exceptional, and how to think about AI in that context.
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Types of AIPart one of a series distinguishing types of AI before using them in clinical work.
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Types of AIThe predictable, the explainable, and its clinical traps.
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Types of AIMachine learning, probability, and the end of absolute clinical certainty.
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Types of AIDeep learning, explainability, and ethical limits between support and delegation.
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Public health and AIOpportunities, limits, and conditions for responsible use in public health.
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