Special Article
The long journey of artificial intelligence in medicine: an overview
E. Grossi1
- Villa Santa Maria Foundation, Tavernerio, Italy. enzo.grossi@bracco.com
CER18707
2025 Vol.43, N°5
PI 0815, PF 0821
Special Article
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PMID: 40338059 [PubMed]
Received: 11/03/2025
Accepted : 16/04/2025
In Press: 08/05/2025
Published: 08/05/2025
Abstract
Artificial intelligence (AI) has its roots in the history of philosophy and of applied mathematics of the 17th, 18th and 19th centuries. Throughout the 20th century, significant advancements in mathematics and computer science laid the groundwork for modern AI, culminating in the establishment of the field as a formal discipline during the Dartmouth Conference in 1956. This pivotal event brought together leading researchers who envisioned creating machines capable of simulating human intelligence, setting the stage for decades of research and innovation in the field. The development of early AI systems focused on problem-solving and symbolic reasoning, leading to the creation of programmes that could play games like chess and solve mathematical equations, which show-cased the potential of machines to perform tasks previously thought to require human intellect. As these foundational systems evolved, researchers began to explore more complex algorithms and learning models, paving the way for advancements in machine learning and neural networks that would eventually revolutionise AI applications across various fields among which medicine. The growth of big data and increased computational power further accelerated these advancements, enabling machines to analyse vast amounts of health information and learn from patterns at unprecedented speeds. The revolution of deep learning and soon after large language models has enabled machines to achieve remarkable feats, such as image and speech recognition, natural language processing, and even creative tasks like art generation, pushing the boundaries of what was once thought possible. As organisations grapple with these challenges, there is growing emphasis on developing frameworks that ensure responsible AI deployment while maximising its potential benefits for human health.
