Technology has advanced, but it does not benefit everyone equally. Especially in the medical field, disparities are directly related to life. The population is decreasing, and medical personnel are concentrating in metropolitan areas. In small and medium cities or remote areas, doctors are disappearing even before hospital beds. As chronic diseases increase with an aging population, it becomes challenging to get a single consultation. Missing the ‘golden time’ in emergency situations is becoming alarmingly common.
The medical gap is now a structural issue. Artificial intelligence (AI) is gaining attention as a new solution to bridge this gap. AI now goes beyond simple assistance and is involved in overall diagnosis, prediction, and decision-making processes. Image analysis, voice recognition, and prognosis prediction technologies are notably effective in reducing errors caused by lack of experience or manpower shortages.
AI medical technology is divided into two main areas. One is the hospital-centered image diagnosis support system, which quickly interprets signs of pneumonia, stroke, cancer, and more from CT, MRI, and X-ray images. The other is the prediction and monitoring system based on everyday life, which collects real-time health data from devices like smartwatches or glucose meters, analyzes patterns, and warns of risks in advance. This makes a significant difference, especially in diseases where early response is crucial, such as hypertension, diabetes, and heart disease.
In rural areas, it’s not just a convenience but a ‘minimum lifeline.’ In fact, in some regions, AI-equipped image diagnostic systems are installed in remote health centers, allowing images to be taken and interpreted remotely. In urgent cases, the AI assesses the level of urgency to decide on transportation. This can be the only solution to securing the golden time in regions with inadequate professional manpower.
AI also offers meaningful opportunities in responding to infectious diseases. After COVID-19, AI’s potential was confirmed in identifying high-risk groups, predicting transmission paths, and distributing vaccines. Recently, efforts are being made to apply AI-based simulation systems to predict the spread of new infectious diseases linked to climate change.
However, AI-based technology is not a panacea. The accuracy of medical AI largely depends on the quality of its training data, and there is still the potential for data bias or errors. Moreover, there is a lack of social consensus on entrusting the highly ethical task of ‘medical judgment’ to technology. Clear guidelines are needed on when and how medical professionals should accept AI-derived decisions.
The most practical barrier is the regulatory system. Remote healthcare and non-face-to-face diagnosis based on AI are restricted by medical laws in South Korea. Although the technology is ready, the irony remains that the law and system have not yet caught up. Under the current situation, technology could end up being just an ‘exhibition innovation’ that cannot be utilized.
AI does not replace doctors. However, in places without doctors or in moments where judgment is precarious, it can play a decisive role. Technology creates ‘possibility,’ and institutions turn that possibility into ‘reality.’ For AI medical technology to function in every alleyway or village across the nation, regulations and policies must support it.
What is needed now is not just the advancement of technology. Technology still needs to become more sophisticated, while its benefits must be accessible to everyone. Life and health should not vary depending on geography or income. To realize these possibilities, technological advancement and institutional support must be achieved simultaneously. What is needed now is ‘execution,’ not ‘preparation.’