Dr. Rohit Sud - My experience using AI to help a patient navigate his cancer diagnosis and treatment

I have been practicing oncology for over ten years, and while my passion has always been rooted in the human side of medicine—offering empathy, explaining complex diagnoses, and guiding patients through some of their darkest moments—I’ve always been open to using technology to improve patient care. When artificial intelligence (AI) tools came around to assist in diagnosis and treatment planning, I was eager to see how they could enhance my practice. I want to highlight my recent experience where I found the impact of AI to be transformative.

Mr X was a 58-year-old man who had been experiencing vague abdominal pain for months. At first, he thought it was just indigestion, but when the pain worsened, he sought medical attention. After several tests, including a CT scan and biopsy, he received the diagnosis he had feared: stage 3 colorectal cancer. Notwithstanding, as a father of three young children, he was overwhelmed. The fear and uncertainty in his eyes were palpable when he walked into my office to discuss the results.

“Dr. what does this mean? What happens next?” he asked, his voice trembling.

It’s never easy to deliver such news, but my role wasn’t just to explain his diagnosis—it was to guide him through the next steps, ensuring that he felt supported and informed. I knew we had to start with a clear understanding of his cancer and explore the best treatment options available. Patients in my experience have always gone to the abyss of the internet to get information that may not be applicable to them, and I wanted to guide him and his family to a more informed internet. That’s when I decided to use the AI tools available to me, tools that I’d been integrating into my practice over the past few months.

Early detection and diagnosis: A second set of eyes

While we had already confirmed Mr X’s diagnosis, I wanted to ensure we had the most comprehensive view of his cancer’s extent. His tumor was located in a tricky area of the colon, and I was concerned about the potential spread to nearby lymph nodes and organs. To get a clearer picture, I used one of the AI-powered imaging tools with the help of my radiology colleagues. This system could analyze CT scans, MRIs, and PET scans much faster and with greater precision than the human eye could.

“Let’s take another look at your scans,” I said, trying to reassure him. “This tool helps us see things more clearly, and I want to be thorough.”

The AI instantly processed his CT scan, providing a detailed analysis of the tumor and its potential spread. When I examined the results, I was taken aback. The AI flagged a secondary nodule in Mr X’s liver that hadn’t been clearly visible in the original scan. While it wasn’t conclusive, this additional information was crucial—it meant that we needed to conduct further tests to understand whether the cancer had metastasized.

“This is why I love using this system,” I exclaimed, pointing to the flagged area on the screen. “It’s like having a second pair of eyes, ensuring that we catch every detail. This finding might change the way we approach your treatment, but let’s take it one step at a time.”

Mr X seemed comforted by the explanation and was intrigued by my open technological approach to his treatment. I could tell that the AI’s precision had given him a sense of confidence. We would still need more tests, but now we were better prepared for what lay ahead.

Personalized treatment planning with AI

After confirming the diagnosis and staging, we needed to decide on the best course of treatment. For someone like Mr X, with a tumor in the colon and potential metastasis to the liver, there were multiple options—chemotherapy, radiation, surgery, or a combination of these treatments. The treatment decisions could be overwhelming, and he wanted to make sure he was pursuing the most effective plan for his specific situation.

I turned to another AI-powered tool I had been incorporating to help develop personalised treatment plans. This system analyzed patient data, including medical records, clinical trials, and past patient outcomes, to recommend tailored treatments based on a person’s unique medical profile. The AI’s ability to cross-reference a wealth of information was invaluable.

“Mr X, here’s where we stand,” I said, pulling up the data on my computer. “The AI has analyzed your condition and compared it to thousands of cases similar to yours. Based on this information, here are a few treatment options we could consider.”

The AI tool provided several recommendations, each with an estimate of success rates and potential side effects. It suggested a combination of chemotherapy and immunotherapy, treatments that had shown promising results for patients with Mr X’s stage and type of cancer including analysing the genetic subtype and targets.

“While we’ll discuss this more in-depth, I wanted to share these insights with you,” I continued. “The data is coming from a massive database of patient outcomes, and it gives us a clearer idea of what might work best for you.”

Mr X nodded, looking at the recommendations thoughtfully. The AI’s data-driven approach allowed him to see exactly why certain treatments were being recommended. It wasn’t just me telling him what to do—it was a collaborative decision based on real-world data, and I could tell it made him feel more confident in his treatment plan.

"I like that I can see the reasoning behind each option,” he said. “It feels like we’re making an informed decision, not just guessing."

Monitoring progress and adjusting treatment

The value of AI didn’t stop at the treatment planning stage. Once Mr X began chemotherapy, I used an AI system to monitor his progress and track his response to the treatment in real time. This system constantly analyzed his lab results, scans, and symptoms, comparing them to other patients with similar profiles. It could predict whether the treatment was effective or if adjustments were needed.

After Mr X’s third round of chemotherapy, the AI system flagged an issue: his white blood cell count was dangerously low, which could leave him susceptible to infection. The system suggested early intervention, advising me to adjust his chemotherapy regimen and start medication to help stimulate his immune system.

"This is why I rely on AI,” I thought to myself. “Without it, I might not have caught this until it was too late."

I immediately adjusted his treatment plan, ensuring he had the right medication to boost his immune system and avoid complications. Jonathan was grateful that we had caught the issue early, and we continued to monitor his progress closely.

The final outcome

After months of treatment and careful monitoring, Mr X reached remission. We celebrated together—relieved, exhausted, but deeply grateful for the progress we had made. While AI had played a pivotal role in his care—offering early detection, personalized treatment, and real-time monitoring—it was the trust we built and the support I provided that made the most difference.

"I don’t know where I’d be without you, Dr. ,” he said as he finished his last round of treatment. “I feel like you gave me a real chance to beat this, and the AI tools helped me understand the whole process."

I smiled, feeling a deep sense of satisfaction. The combination of cutting-edge technology and compassionate care had led to a successful outcome for Jonathan. As a doctor, it reaffirmed my belief that technology can complement human care, but it’s the human connection that ultimately drives patient success.