Modern technologies accompany us at every step of life. It is therefore no surprise that they have long entered the field of medicine. Their potential is enormous, and it is worth using them extensively, from diagnostics to treatment and management. This can help mitigate some of the challenges faced by healthcare systems, such as the chronic shortage of medical personnel. This issue is discussed in the latest publication by General Grzegorz Gielerak, Director of the Military Institute of Medicine in Warsaw (WIM), one of the leading authorities in the field of military medicine.
Medicine is Constantly Evolving
Diseases, their progression, treatment methods, tools and means used, medical care, therapy, and healthcare facilities, all are evolving. The pace of life continues to accelerate, and no one understands the importance of instant decision-making, decisions that can affect human life and health, better than a physician. Support for this sector is therefore of particular importance: for doctors, the patients, and for the healthcare system as an institution.
Modern solutions in artificial intelligence (AI) and robotics are coming to the rescue. Although AI is still a field many are only beginning to understand, its potential is immense and undoubtedly worth harnessing.
AI is Already in Medicine
This subject is addressed in an article by Gen. Grzegorz Gielerak, published in the periodical “Menedżer Zdrowia” (Health Manager), titled “Artificial Intelligence and Robotics in Practice.” The expert discusses numerous issues related to modern technological solutions in medicine. He points out that back in 2016, there were approximately 6,800 publications on the use of AI in healthcare, whereas last year there were 28,000. It is hard to find a better indicator of how rapidly this technology is developing and how widely it is being adopted in medicine. AI is already present, particularly in the field of diagnostic interpretation.
“An increasing number of clinical studies, including randomized controlled trials (RCTs), confirm the effectiveness and innovative potential of AI-based medical solutions. An analysis of 39 RCTs showed that in 77% of cases, AI use outperformed standard medical care, and in 70%, it led to clinically significant improvements, such as earlier detection of pathological changes in radiological or endoscopic imaging,” notes Gen. Gielerak.
In his publication, Gen. Gielerak emphasizes that “in safety monitoring, machine learning systems can detect up to 92% of adverse events up to 48 hours earlier than conventional methods. Moreover, the applications of AI are no longer limited to clinical research – they now encompass the entire spectrum of healthcare systems: from strategic medical resource planning and support in pharmaceutical processes to decisions made directly at the patient’s bedside.”
AI also plays an increasingly important role in the pharmaceutical industry. Algorithms monitor supply chains and manage strategic reserves, enabling early detection of threats and optimal distribution of products during crises. At the same time, they automate successive stages of clinical research, from participant qualification and ongoing monitoring of efficacy and safety to data analysis, collectively reducing the time needed to bring innovative molecules to market and strengthening the sector’s competitiveness.
Collaboration Between Humans and Technology
Technology is meant to support the physician – to facilitate decision-making and prepare data that leads to accurate diagnoses. “The key model for integrating AI systems in medicine is the human-in-the-loop (HITL) approach, which assumes continuous collaboration between humans and artificial intelligence in clinical processes. This concept ensures that advanced algorithms assist medical decision-making while remaining under expert supervision,” writes Gen. Gielerak.
“In diagnostics, particularly in radiology and oncology, AI algorithms can rapidly analyze vast sets of medical data, such as imaging or laboratory results, detecting subtle abnormalities invisible to the naked eye. This undoubtedly speeds up the entire process while relieving the burden on medical staff. Another area is treatment optimization. Algorithms can predict the effectiveness of therapeutic interventions or suggest treatment plans based on the analysis of large datasets,” the expert explains.
AI technology can also effectively analyze individual patient characteristics, from genetic predispositions to lifestyle habits and behaviors, and, based on that data, propose specific actions.
“Recent studies confirm that AI algorithms in medical diagnostics often achieve sensitivity and specificity levels comparable to those of physicians, particularly less experienced ones, and, in some cases, even surpass them,” emphasizes Gen. Gielerak.
It is worth noting, however, that the effectiveness of AI still depends on the specific specialization and clinical application area.
Three Key Segments
General Gielerak identifies three main areas of AI application in the medical sector, depending on the level of clinical maturity:
1. Routine Operations
- Analysis of radiological images
- Digital pathology (classification of cancer cells based on digital histopathological slides)
- Support for pathologists in daily diagnostics
- Monitoring in intensive care
- Cardiological diagnostics
2. Ready for Broader Implementation
- Personalized oncology therapy – recommending treatment regimens and targeted drug dosages based on large patient databases
- Early stroke diagnostics
- Diabetes care – algorithms adjusting insulin doses based on continuous glucose monitoring
- Robotic assistance in orthopedics – surgical support for precise prosthesis implantation and spinal stabilization
3. Future (Experimental) Solutions
- Autonomous surgical robots – systems capable of recognizing anatomical structures and performing selected surgical stages under a surgeon’s supervision
- Digital battlefield triage – algorithms classifying the wounded according to mortality risk based on soldiers’ vital sensor data, aiding medical aid prioritization
- Virtual clinical trials – “digital twins” of patients simulating various therapy scenarios in silico, optimizing treatment selection before human trials
- Empathetic medical chatbots – assistants based on large language models, supporting patient interviews and education
As Gen. Gielerak notes, “Delegating up to 80% of routine image and laboratory analyses to AI could free human resources, allowing medical staff to focus on comprehensive patient care.”
Keeping Humans at the Center
Humans must remain the central decision-makers. “It is the physician, guided by empathy, experience, and ethical reflection, who bears responsibility for the patient’s health and life,” Gen. Gielerak stresses in his conclusions.
Can we harness the potential of artificial intelligence without losing the humanistic dimension of medicine? That question remains open. “What is certain, however, is that only by maintaining cognitive and moral vigilance can we build a system in which technology serves humanity, and not the other way around,” he adds.
It is worth keeping this in mind, not only in medicine.