Time, Technology, and Touch: Rethinking Medical Practice in the Digital Age
Since the beginning of medicine, healing has been a deeply human act. In ancient Greece, Hippocrates first defined a professional ethics and a practice centered on the observation of the body and its symptoms (1). In the Middle Ages, monasteries preserved and transmitted medical knowledge, where the care of the soul and the body were intertwined (2). In the 17th century, Antonie van Leeuwenhoek inaugurated a new era with his microscope, revealing invisible worlds and forever changing the way we understand illness (3). Medicine has constantly evolved, incorporating tools that have expanded the senses of the physician: stethoscopes to hear better, images to see the hidden, algorithms to anticipate the probable. Today, we are living another revolution. From the creation of the Perceptron in 1958, the first rudimentary model of a neural network, to the emergence of natural language models like GPT and the application of deep learning in medical images, artificial intelligence has ceased to be a futuristic promise (4-7). It is now an active part of the clinical environment. We are told that algorithms diagnose more accurately than the human eye, that systems can draft notes in seconds, and that conversational models will soon guide the patient's anamnesis. And in the face of this, many feel unease and uncertainty.
I trained as a physician amid this transition. I am a final-year student, and throughout my journey, I observed closely how society transformed with the integration of new technologies. This transformation led me to ask questions. From the first semester, I was driven by an insatiable curiosity for everything that still lacked concrete answers. The classes, vast and fascinating, provided me with solid foundations, but I searched in the margins: in biochemistry, in neuroscience, in surgery, and in cardiology, where the notes fell short. I immersed myself in clinical databases, read books outside the curriculum, and sought conversations with physicians who challenged the status quo. I did this not only to know more but to be prepared when I would finally face the privilege of caring.
It was then that AI was just beginning to emerge as a disruptive tool. Its impact on clinical practice and our society generated a concern that I shared with my colleague Pablo Pineda. Together we founded the first seedbed of artificial intelligence applied to medicine at our university. We did not do it from a place of empty technological enthusiasm but from a deep necessity: to think critically. We wanted the faculty to have an academic space that allowed us to enter this new era with a critical gaze. We asked ourselves what ethical, political, environmental, and public health implications this change would have. Because if it weren’t us who asked those questions, others would decide for us.
With the support of internist Andrés Rico and the director of the Master's in Artificial Intelligence Leonardo Flores, we created an interdisciplinary space where medical, dental, biomedical engineering, and systems students could engage in dialogue. We discovered that fear of AI often arose from ignorance. Understanding was the first step to dismantle that fear. And in that process, we arrived at a powerful truth: artificial intelligence does not come to replace the physician but to offer them a choice. The choice to reclaim their time, that scarce and valuable resource, to return to what truly matters: to think, diagnose, and care.
From that thought emerged a specific question: what if we could design an AI that helped the physician with their administrative tasks? Not to make them do more but to make them do better. So that their gaze returned to the patient's eyes, not to the screen. With that idea in mind, I participated in the national Shark Tank of the Colombian Surgery Association, along with biomedical engineer and physician Santiago Suárez Gómez, who also began seeking ways to provide better care to patients by uniting his two undergraduate degrees. We presented a project that is now a company. We set ourselves a bold mission: to return to the physician their most precious asset: their time. Together with internal doctors Mateo Uribe and Lucía Rocha, we designed an AI centered on the clinical language of the professional, not on bureaucracies. A real assistant, sensitive to context, that would automate what was necessary and liberate what is essential. What began as an idea gradually materialized into something real. Winning the contest was gratifying, but the truly valuable thing was understanding that we could build something that concretely helped those who practice this vocation.
In this process, neurologist Juliana Coral believed in our idea. Thanks to her and the team from the neurology department, we achieved something improbable: bringing this idea to the hospital, starting a real protocol, and beginning to materialize what was once just a shared vision. Beyond the faculty, the university did not lag behind. They provided a space to analyze the challenges of AI and chose Pablo and me to think alongside them. Pablo and I were invited to the University Reflection Day alongside the rector and academic leaders from various faculties. We not only spoke of medicine, but integrated knowledge from different fields regarding how the teacher-student relationship would be affected, the transformation of thought, and the role of the human. There, among different disciplines and generations, we asked ourselves: how do we protect what is essential without clinging to the past? It was an honest dialogue, questioning what data trains the algorithms, what biases they carry, what decisions they automate. And, above all, who gets left out when we let machines decide for us.
In this, my curiosity was awakened regarding the role that AI would play in more concrete issues, and I allowed myself to research in areas that generated interest. One of my projects was accepted for a conference at the annual meeting of the American Academy of Neurology in San Diego, California, on the use of AI to improve the diagnosis of alterations in the state of consciousness based on neuroimaging. There, I presented not only data but dreams: those of a medicine that thinks more accurately without ceasing to feel. This work was made possible thanks to an invaluable support network: Dr. Gabriel Castellanos, psychiatrist Hernando Santa María, neurosurgeon Juan Carlos Acevedo, resident Andrés Ricaurte, and my colleagues Salomón Páez and Kiara Torres, also interns, and Dr. Adriana Buitrago who helped me understand the care that a review of that level requires. They taught me that science is not a solitary race but a collective effort, where the project received great support from prominent figures from various institutions, including the neurologist practicing at Harvard, Liliana Ramírez, who accompanied me when I gave my presentation. After which I shared with neurologists like Diego Cadavid, Lucas Restrepo, and Miguel Ángel Hernández, with whom I discussed research, challenges, and changes in AI in neurology.
But not everything was science. There were days when the emotional burden of clinical rotations overwhelmed me. Being in contact with patients made me understand that understanding the pathophysiology behind a disease was far from sufficient. That sometimes probabilities play against us despite more technology, more medications, more strategies. Attending to patients is an act of humanity challenging nature, and sometimes, more often than we would like, we are left with all our effort in hand with the only peace that we gave it our all, as the distinguished Dr. Álvaro Ruiz teaches in his classes that accompany me in my day-to-day life. There was a patient I took to the emergency room trying to pull her away from death. I wanted that young, sweet girl with whom I laughed, who told me she was getting married in two months, who had a job interview the next day, to be able to achieve all that she firmly believed she would do in her clinical history interview. "2:34 AM, time of death," I wrote while drafting the case note. Patients arriving injured, whose parents told them they probably wouldn’t wake up. But I also observed a baby who required intensive care dress up as a princess and leave the hospital enthusiastically. Surgeries where teachers managed to save patients with blood pressure readings that seemed to indicate it wouldn't happen.
I observed how at such moments, even when it seemed there was no solution, the patient smiled when listened to with understanding and kindness, not as just another illness but as a person. In those moments, like when I wrote my first certification of dysfunction in internal medicine, doctors like Santiago Grillo, with his charisma and diligence, showed me that being brilliant goes hand in hand with being compassionate. That not obtaining the expected result was not failing the patient; it was a reality that we are responsible for making the humanly possible with what science allows us. That long night shifts are brightened with a smile, that patients value doctors like the rheumatologist in training, María Higuera, who treat them with calmness and affection. All the experiences from each shift since I started my practices in the fifth semester until my clinical internship led me to feel that it is worth continuing to get up early to see patients, to read their unique and special stories, to keep asking my teachers, and to literature, to continue with my curious mind driven to keep writing and researching. Because a published article can also be a way to care, contributing to the generation of new knowledge for the scientific community.
I remember how in my first open-heart surgery, Dr. Giovanny Ríos, a cardiothoracic surgeon, told me, "I would not allow you to accompany me without being certain first, that you are academically prepared, and second, that I can guide you." I felt delight and euphoria at having participated in something so beautiful. As the vascular surgeon Felipe Cabrera mentioned to me: Medicine is where art converges with science. I told him, with a nostalgic smile, that I had been dedicated to other disciplines before. That I gave piano recitals, did commissioned portraits, and won sports tournaments. That sometimes I missed getting lost in scores, music concerts, novels, or cheerleading uniforms. But I found more beauty in science than in art, I told him. He looked at me as he adjusted a knot in the workshop and replied: "Here you are already doing both." That phrase still accompanies me, because indeed: medicine is an art. One that is practiced with attentive ears, compassionate gaze, and precise hands. An art that for centuries had silence, words, and touch as its instruments. Today, we add screens and data. But the essence does not change. What heals is not the algorithm: it is the relationship with our experience. We are entering a new stage of medicine where physicians will use intelligent tools with judgment and limits. Where AI will not replace the hand of those who practice this, but will support or challenge their judgment at times, offer different perspectives at others, and facilitate administrative tasks where needed: where it will not automate the doctor-patient relationship but the paperwork. Where it will not displace the physician but enhance them. Because, if designed consciously, integrating it into our protocols and guidelines, artificial intelligence can come to remind us that the center has always been the patient, not the system or how it will be approached.
We are at a historic crossroads. Medicine, as in other moments of its history, when it discovered the first germs, when it mastered anesthesia, when it learned to see inside the body, is changing. But not everything new is progress, nor is everything ancient obsolete. Understanding is the first step to setting aside blind fear and starting to work together on how we can integrate knowledge into our practice. Remember that curiosity can change the world, that knowing how to design a question can make the difference in how we practice our clinical work. That we do not have to wait until we graduate to create. Allowing the desire to help and serve to be greater than staying doing what is expected of me. Because with persistence and discipline, one can organize schedules to gradually realize dreams, which have more strength when built as a team. Everything I have lived and accomplished at each stage has been supported by more people than I can write in this column. To all those with whom I have collaborated, each doctor who has taught me, guided, and accompanied me. My family and friends who do not allow me to stop. Those who let me fail and learn. Those who believed in my ideas and were by my side even when it seemed I was not progressing. They reminded me that amid this path full of challenges, there is beauty in the uncertain. A fragile beauty, yes, but powerful where we solve puzzles and give quality of life or death as allowed and appropriate. I dream of graduating in an environment that practices precise and tender medicine; efficient and compassionate. That integrates technology without losing the art. Because humanity is not an obstacle to progress. It is its north. Artificial intelligence can change the way we practice medicine just as all other disciplines of knowledge that are challenging the resilience of their professionals. It can change how it is practiced, as long as it does not affect why.
AI will not save the patient. The physician will do that, who, thanks to it, had greater access to different criteria when in doubt, or simply had a little more time to look into their eyes instead of writing notes. The patient will not remember the clinical guide used to treat them. But they will remember if their condition was explained, good or bad, calmly. They will remember who touched their shoulder. They will remember who was there to listen to their fears. Yes, AI is a resource that provides precision, but I am convinced that medicine is something that no algorithm can do for us. We do not have to understand it all today, just keep walking despite the fear, supported by those who are on this journey with us. And maybe that is all that is needed: the decision to continue caring, even with the changes that time brings.
References
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Esteva A, Robicquet A, Ramsundar B, Kuleshov V, DePristo M, Chou K, et al. A guide to deep learning in healthcare. Nat Med. 2019;25(1):24–9.
Brown T, Mann B, Ryder N, Subbiah M, Kaplan J, Dhariwal P, et al. Language Models are Few-Shot Learners. Adv Neural Inf Process Syst. 2020; 33:1877–901.
