Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
ALGORITHMIC, UNDIFFERENTIATED AND DIFFERENTIATED THINKING IN MEDICAL PRACTICE
0
Zitationen
2
Autoren
2024
Jahr
Abstract
This article discusses different ways of thinking used in medical practice. Authors analyze questions concerning medical decision making, and examine impact they have on quality of medical care. First kind of thinking under inquiring is algorithmic thinking. It is used by doctors when they adhere to algorithms and protocols in making decision. Algorithms can standardize diagnosis and treatment process, which can reduce risk of error and improve efficiency of medical assistance. However, algorithmic thinking can lead to standardized approaches, having as consequence ignoring of individual patient characteristics. Second kind of thinking that shall be examined is undifferentiated thinking. Undifferentiated thinking can lead to missing important diagnostic signs and inappropriate treatment based on subjective assumptions. Third kind of thinking discussed in the article is differentiated thinking. Using this kind of thinking, doctors take into account individual characteristics of each patient and apply flexible approaches to diagnosis and treatment. Differentiated thinking allows health care to be tailored to a specific situation, which may increase its effectiveness. However, differentiated thinking requires that doctors ought to have in-depth knowledge and experience, as well as the ability to analyze complex medical data. The article discusses relevance of different kinds of thinking in medical practice and encourages doctors to develop their differentiated thinking skills. It shall improve quality and efficiency of medical care by taking into account individual needs of each patient.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.336 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.207 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.607 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.776 Zit.
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
2018 · 5.476 Zit.