Pulse and hopes high when healthcare and Al hold hands
3 June 2025 01:00
EISSA ALI ALMANNEI *Technological progress sometimes affects human lives slightly and sometimes in profound ways. But when it empowers vital sectors like healthcare, the hopes pinned on this technological revolution increase. This is exactly the case with harnessing artificial intelligence in the healthcare industry and the adoption of AI tools by healthcare institutions to assist at every stage of the care process.Large language models, chatbots, and voice assistants are now integrated into AI-powered workflows across clinics and hospitals, helping in internal processes and medical records. AI can improve operations, from human resources to insurance claims, facilitating data management and applying AI tools to generate automated reports and resource utilisation metrics in real time.This saves a lot of time on administrative tasks and interactions while reducing costs. AI is not limited to administrative and financial operations. In fact, it can give anonymous patient data, such as MRI scans, CT images, lab results, and clinical notes, to feed AI diagnostic tools.In radiology, AI helps doctors transcend the limitations of the human eye, as it trains algorithms to reconstruct blurry images and highlight areas of concern, such as tumors or fractures. With big data and patient record analysis, healthcare professionals can detect patterns and risk factors that might be missed in traditional diagnostic methods.One of the fundamental advantages of AI in healthcare is its ability to improve diagnostic accuracy and treatment plans, which enables faster decision-making by providing physicians with precise, real-time information. In emergencies, where time is critical to saving lives, AI-assisted robotics can improve surgical outcomes, aid surgeons in enhancing precision, reduce complications, and improve patient recovery.In the pharmaceutical sector, companies rely on AI to analyse chemical composition databases, protein interactions, and side effects. This not only accelerates drug development but also increases the success rate of new medications while improving safety and reducing the risk of adverse reactions. AI can even predict individual responses to treatments by analysing genetic profiles and medical histories and discovering how a specific gene variant affects drug metabolism.In addition, AI can simulate patients in clinical training, allowing students to adapt to various cases. Virtual patients respond in real time to what the student says or does, creating a more realistic experience. AI is also being used in mental health, guiding cancer survivors through post-treatment care, and assisting in the early detection of diseases, including certain types of cancer.Although AI is still relatively new in healthcare, there is now a smart hospital in China operated by fourteen AI-powered virtual doctors who diagnose and treat patients without any human staff. This virtual team is capable of treating over 3,000 patients daily. This implies that AI's ability to match, or even exceed, human diagnostic capabilities in terms of accuracy and speed is within reach.However, there are challenges related to the ambiguity of AI models to physicians, making it difficult to understand how they arrive at conclusions. This lack of clarity can confuse doctors when they cannot grasp the reasons behind an algorithm's diagnosis.Moreover, there are concerns about protecting patients' medical privacy, as AI relies on massive datasets that frequently contain sensitive health information. AI outcomes can also be biased due to disparities or differences in training data, leading to distorted results. Therefore, the quality and balance of the data used to train these models are critical to ensuring accurate and reliable results.The hopes for AI in healthcare are undeniable. Medical AI systems can process information faster than any human doctor, but caution is needed to address challenges, use data analysis and advanced analytics, and continue developing technologies that aid in disease diagnosis, prevention, personalised treatment, and drug development to improve the quality of human life.
* The writer is a researcher at TRENDS Research & Advisory
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