We no longer have to imagine a world where diseases are diagnosed instantly, surgeries are performed with pinpoint precision, and life-saving drugs are discovered in a fraction of the time. The future is already starting to unfold as technologies enabling these breakthroughs are being developed and put into use. While still in the early stages, the potential to revolutionize healthcare is imminent.
Artificial intelligence (AI) is advancing the medical field in ways that are already saving lives and transforming healthcare and research. Among the technologies converging to change the industry, AI stands out as the most disruptive. Innovations in mobile technology, the Internet of Things (IoT), computing power, and data security are joining forces with AI, impacting everything from medical equipment and drug delivery to patient care.
AI helps create intelligent machines that learn from experience and mimic human cognition, continuously adapting as they process new data. This capability stands to meet future needs in the healthcare industry. According to a World Health Organization report, by 2030, there will be 10 million fewer healthcare professionals than needed globally.[1] While AI is still in its early phases, its potential to bridge this gap and transform medicine is undeniable. Here are six exciting ways AI is already making a difference.
1. Diagnostics
One of AI’s most exciting applications is in diagnostics. AI systems can help diagnose and predict diseases faster and more accurately than many medical professionals, significantly reducing fatal human errors caused by incomplete medical histories and heavy caseloads.
2. Pharmaceutical Research
New drugs require high development costs and thousands of human hours. Consequently, only 10 percent of drugs that make it to clinical trials come to market. However, AI breaks down data silos and accesses information that recently took years to process. As a result, AI is now speeding up this research process by designing drugs, predicting side effects, and identifying candidates for clinical trials.
3. Robotic Surgery
Robotic surgery, already well-established, is enhanced by AI, which helps automate workflows and improve clinical decision-making. From minimally invasive procedures to complex heart surgeries, AI-driven robots are setting new standards in precision and efficiency.
4. Targeting Bacterial DNA
A recent breakthrough reported by Singularity Hub highlights AI’s role in identifying nearly a million potential antibiotics to combat superbugs. As bacteria rapidly mutate, AI accelerates the discovery of specific drug candidates, offering a powerful tool against resistant strains.
5. Improving Imaging Precision
AI delivers precision image quality, minimizes patient mispositioning, and even reduces radiation doses in CT imaging. For MRIs, AI speeds up exams, boosts diagnostic confidence, and cuts costs. It also automates repetitive tasks in ultrasound imaging, allowing radiologists to read images faster and more accurately.
6. Early Deterioration Detection
AI provides the ability to rapidly detect severe postoperative events that occur in medical-surgical nursing, compared to the time it takes to identify problems through manual patient monitoring. This can help prevent postoperative complications that lead to extended hospital stays.
Overall, AI enables doctors to make faster and more accurate diagnoses, health administrators to access electronic health records faster, and patients to receive more timely and personalized treatments. Yet, we’re still at the dawn of what AI can do and how we handle it.
Ethical Considerations
Despite these various healthcare advancements, AI is not necessarily a clear path forward. There are ethical concerns about the current state of AI in medicine and its future. AI has the intelligence for analysis, problem-solving, and decision-making, but with this intelligence comes numerous ethical considerations. These include potentially biased data, inaccurate information, incorrect health-related responses, lack of consent for large language model (LLM) use for training purposes, privacy and security issues with patient health data, the potential for highly convincing disinformation, and policy decisions ensuring patient safety that may be lagging behind the push to capitalize on the technology.
AI-generated LLMs include rapidly expanding platforms imitating human capabilities. Usually, new technology—especially in the medical field—is subject to rigorous evaluation and supervision. However, this regulation is not applied consistently to LLMs. Unfortunately, this could lead to high-profile errors that, depending on their magnitude, could erode trust in the technology’s use.
There has been early guidance on the use of AI in healthcare, which could help pave the way for regulatory measures going forward. The World Health Organization published Ethics and Governance of Artificial Intelligence for Health, which identifies six core principles:
- Protect autonomy
- Promote human well-being, human safety, and the public interest
- Ensure transparency, explainability, and intelligibility
- Foster responsibility and accountability
- Ensure inclusiveness and equity
- Promote AI that is responsive and sustainable
While AI is becoming a transformative force in health care, guaranteeing ethics may be a juggling act, at least in the near term.
Medical AI’s Future
While ethical challenges will always be present, AI’s future in medicine is promising. Treatment outcomes will improve, human error will decline, and healthcare costs will decrease. AI stands to enhance diagnostics, drug discovery, and overall healthcare efficiency. AI will not replace physicians, but it will augment their capabilities, allowing them to make higher-level decisions and collaborate with AI systems. As patients and healthcare professionals recognize AI’s potential to improve health outcomes, its use will continue to grow, and the potential gains for the healthcare industry are significant.
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