Applications of Artificial Intelligence and Data Science in Healthcare

Artificial intelligence (AI) is a technology that enables computers to mimic human-like learning, reasoning, and decision-making processes. When we look at the responses of the AI tools we use today, we often see that they are numerical, comparative, and science-based. In this sense, AI is a system that produces completely data-driven results, independent of emotions. Sometimes, you might even find yourself nudging AI to give more emotional or personal responses. Perhaps that’s what natural intelligence truly is… Because AI is designed to interpret and conclude based solely on the data it has, without mixing in emotions.

Due to this very characteristic, AI applications in healthcare, which require high precision and rationality, are of great importance. This is where data science comes into play. Data science aims to process large amounts of data and extract meaningful insights. When AI and data science combine, they bring groundbreaking innovations to the healthcare sector. Today, examples of AI in medicine range from early disease detection to the development of personalized treatment plans.

From the moment you book a hospital appointment, every detail—your name, surname, age, and the hospital and department you booked—is actually data. Imagine if AI could analyze this appointment data and notify you when it’s time for your check-up—wouldn’t that be great?

Similarly, let’s consider doctors. In our country, consultation times have fallen below even five minutes. In such an environment, AI applications could summarize all your test results, medications, and lifestyle habits during your illness and quickly relay this information to your doctor, providing a second expert opinion. This would significantly speed up and simplify the treatment process. Yes, all of this is possible thanks to AI and data science, and it is already being used in healthcare today. Let’s look at a few applications of AI and data science in healthcare.

Early Disease Detection

AI offers revolutionary solutions for early diagnosis, especially in radiology and imaging. Today, analyzing MRI and CT images with AI algorithms allows cancers and neurological diseases to be detected much earlier than traditional methods. For example, an AI model developed by Stanford University was able to detect 14 different pathologies in chest X-rays with accuracy comparable to human radiologists (Rajpurkar et al., CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning, 2017). Similarly, researchers at Harvard Medical School reported that deep learning models could identify lesions in breast cancer screenings that human eyes often missed, with over 90% accuracy (McKinney et al., International Evaluation of an AI System for Breast Cancer Screening, Nature, 2020). These examples are just two instances showing how AI in healthcare can be life-saving. When used correctly, AI acts as a second pair of eyes for doctors, increasing diagnostic speed and reducing error rates.

Treatment Planning and Personalized Medicine

Your daily habits, such as diet, sleep, and exercise, also affect the treatment process. AI-powered mobile applications can collect this data and provide personalized nutrition or exercise recommendations. For example, it is possible for an AI-enabled app that continuously monitors a diabetes patient’s blood sugar levels to automatically calculate the correct insulin dose.

Patient Monitoring and Digital Assistants

Illness doesn’t only occur in the hospital; the main process usually continues in the patient’s daily life. Regular medication, diet, sleep patterns, and physical activity play a crucial role in treatment success. However, tracking all this data individually can be challenging for both the patient and the doctor. This is where AI-powered digital assistants and patient monitoring systems come in. Imagine your smartwatch measuring your heart rate and automatically reporting it to your doctor, alerting you to any sudden irregularities… This way, the treatment process is not limited to hospital visits but becomes continuous and personalized healthcare support.

The Future of AI in Healthcare

As we can see, today AI contributes significantly to healthcare, from early disease detection to personalized treatment plans, patient monitoring, and drug development. However, this is only the beginning. In the future, AI-supported hospitals, robotic surgery systems, and fully digital patient monitoring platforms will continue to transform healthcare services.

In my next article, I will discuss projects like EczacıGPT and BrainDetective, which my team and I developed using AI and data science while still students. I hope this article has given you an idea of how effectively AI can be used in healthcare. I am sure it will inspire many new ideas and perhaps even lead you to take a new step in making life easier with AI!