Technology in Medicine

  • A New Epoch in Science: Geoffrey Hinton and John Hopfield’s Nobel Prize in Physics Victory

    Dr. Marco V. Benavides Sánchez. In a remarkable turn of events that signals the increasingly pivotal role of artificial intelligence in our lives, Geoffrey Hinton and John Hopfield have been awarded the 2024 Nobel Prize in Physics. This recognition not only crowns their lifelong commitment to advancing machine learning but also significantly marks the first…

  • Medical and Surgical Education: The Impact of Active Learning Models

    Dr. Marco V. Benavides Sánchez. In the rapidly evolving landscape of healthcare, the importance of effective education for medical and surgical professionals cannot be overstated. As the complexity of medical knowledge and procedures increases, traditional teaching methods often fall short in preparing healthcare practitioners for the challenges they face in real-world scenarios. This is where…

  • Prompt Engineering: The State of the Art and Its Importance in Healthcare

    Dr. Marco V. Benavides Sánchez. Artificial intelligence (AI) is definitely changing healthcare. From diagnosing illnesses to suggesting personalized treatments, AI’s potential is limitless. A relatively new but rapidly growing subfield in AI, known as prompt engineering, plays a vital role in the effectiveness of AI tools, particularly those powered by large language models (LLMs) like…

  • Balancing AI Innovation with Patient Safety

    Dr. Marco V. Benavides Sánchez. Artificial Intelligence (AI) has revolutionized various sectors, and healthcare is no exception. From early disease detection to personalized treatment plans, AI has the potential to transform patient care and outcomes. However, the integration of AI into healthcare systems presents several challenges, particularly in balancing innovation with patient safety. This delicate…

  • The Rise of Computer-Aided Diagnosis (CAD)

    Dr. Marco V. Benavides Sánchez. In recent years, the integration of artificial intelligence (AI) into various medical domains has dramatically reshaped how healthcare professionals approach diagnosis and patient care. One of the most groundbreaking advancements within this domain is Computer-Aided Diagnosis (CAD), a technology that combines AI, advanced image processing, and machine learning to assist…

  • Biomedical Named Entity Recognition

    Dr. Marco V. Benavides Sánchez. Introduction In the ever-evolving field of biomedical research, the identification and classification of entities such as diseases, drugs, and proteins are crucial for advancing our understanding and treatment of medical conditions. Named Entity Recognition (NER) plays a pivotal role in this process by enabling automated systems to recognize and classify…

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This is how it all started…


The beginnings of Artificial Intelligence (AI) represent a fascinating chapter in the history of human thought and technology. They date back to the mid-20th century, when scientists and visionaries began exploring the possibility of creating machines capable of thinking and learning like humans. This quest to replicate human intelligence in machines gave rise to revolutionary advances that have transformed countless aspects of our society and our way of life.

One of the starting points of AI is found in the 1950s, with the birth of modern computing. Pioneers such as Alan Turing, considered the father of computing and AI, laid the theoretical foundations for what would come later. His seminal work on the “Turing Machine” and his famous Turing Test laid the foundation for thinking about artificial intelligence and how we could evaluate it.

However, the term “Artificial Intelligence” itself was coined later, at a 1956 conference at Dartmouth College, where John McCarthy, Marvin Minsky, Nathaniel Rochester, and Claude Shannon, among others, met to discuss the possibility. to create intelligent machines. This historic meeting marked the formal beginning of the AI ​​discipline as a field of study.

Over the following decades, advances in hardware and software laid the foundation for the development of AI. Different approaches and paradigms emerged, from symbolic logic to machine learning and neural networks. One of the early milestones was the development of the chess program “The Turk” in the 18th century, although it was later discovered that it was being operated by a human. However, it set a precedent for the idea of ​​machines that could challenge the human mind in strategy games.

In the 1960s and 1970s, AI saw significant growth, with research and development in areas such as problem solving, natural language processing, and computer vision. One of the highlights was the development of the “ELIZA” program by Joseph Weizenbaum in 1966, which simulated a therapeutic conversation and demonstrated the ability of machines to interact with humans in more complex ways.

During the 1980s and 1990s, AI continued to advance, although it also faced periods of disillusionment known as “AI winters,” where progress seemed to stagnate. However, these periods of stagnation were followed by new advances that revitalized the field. One of the most important milestones of this era was the development of expert systems, which used rules and knowledge bases to imitate human reasoning in specific domains.

The turn of the millennium brought with it a renaissance of AI, driven largely by the increase in computing power and the availability of large amounts of data. Machine learning, and in particular the deep neural network approach, began to bear fruit in practical applications such as speech recognition, machine translation, and autonomous driving.

Today, AI is present in almost every aspect of our daily lives, from online search engines to content recommendation systems and virtual assistants on our mobile devices. It continues to evolve at a rapid pace, with advances in areas such as generative AI, autonomous robotics and explanatory AI, which seeks to make AI systems more transparent and understandable to humans.

Dr. Marco Benavides

Medicine and Surgery