AI helped – When Conno Christou found two blood clots and a fast-growing non-Hodgkin’s lymphoma mass, two top oncologists gave him opposite chemo plans. He collected 12 opinions, used wearables and bloodwork habits to track his treatment, and fed scans into Claude to chal
Conno Christou was the kind of founder who turns health into a dashboard. He wore a Whoop band to track his sleep. cross-referenced it with an Oura ring. and got nearly 100 biomarkers checked every year. For four consecutive years. he’d been doing annual bloodwork. following the longevity playbooks advanced by researchers such as Peter Attia and Rhonda Patrick. His routines weren’t just about supplements and protein intake—he was trying to dial in his circadian rhythm too.
In 2025, his last checkup was green across the board. “It was the best I’d had in years,” he says.
Then, after a workout, his arm swelled.
He didn’t rush to interpret it. A week passed before he saw a doctor, who found two blood clots in his veins and scheduled surgery. The pre-op exams flipped the story. A doctor walked back in and said the procedure wasn’t happening.
“We see an 11-by-11-by-8 centimeter mass behind your sternum,” the doctor told him.
A biopsy confirmed the diagnosis Christou had never imagined he’d face: an aggressive, fast-growing form of non-Hodgkin’s lymphoma. The condition is rare, affecting roughly one in 420,000 people. It’s caused by a random genetic mutation with no connection to lifestyle, diet, or stress. Christou learned the timeline too: the tumor had existed for about three months. and in three more weeks it would have reached stage four.
He now describes the situation in a mix of gratitude and disbelief. “Lucky in my unluckiness,” he told this editor from his home in Athens, where he lives part time. “It was only found because I went in for something else entirely.”
What happened next became a lesson in how medical decisions can pivot—fast—and how much a patient’s choices can depend on the willingness to push for clarity.
His first oncologist, a renowned specialist, recommended the lighter of two available chemotherapy regimens. Christou booked his first infusion three days out. Then, the night before, he sought a second opinion.
That second doctor recommended the harder regimen: continuous in-hospital infusion, cycling every three weeks across six months, based on Christou’s specific pathology. The lighter option carried roughly a 60% success rate for his presentation. The aggressive one brought that number to around 85%.
Two world-class doctors, opposite recommendations.
As founders, Christou said, people often accept what they’re told—and then assume that’s the end of the story. “As founders, we hold the wheel,” he says. “You hear many things. You don’t have to follow the first advice.”
He didn’t treat the second opinion as the final word either. Over the next two days. he gathered 12 opinions in total—pulling from his professional network. reaching out to hematologists and oncologists in the US and abroad. and calling in every favor he could. Eleven to one voted in favor of the harder path. He chose it.
He says the decision didn’t feel brave so much as logical. He’d already built his life around being data-driven. Now the stakes felt existential.
For six months. he approached chemotherapy with the mindset of a builder facing a long project: marathon sprints. each with a finite cycle and each week filled with data points. He’d served 25 months of military service in Cyprus at age 18, and he borrowed from that experience too. He told himself to be a good soldier—trust the process, complete the six cycles.
Throughout treatment, he wore his Whoop band. He found it “remarkably accurate” at predicting days when his immune system would bottom out. sometimes flagging those days before symptoms arrived. He kept a symptom journal using voice transcription, logging every shift, every side effect, every medication and counter-medication. Over time, he narrowed his focus to three variables: sleep, nutrition, and psychology.
Christou put psychology first. “It moves the needle more than anything,” he said. He also described how he refused to get stuck in blame. (“I never asked ‘why me’ — not once. That question has no useful answer.”)
All of it—blood results, scan data, wearable output, journal entries—went into Claude. He’s far from alone in the growing trend of using chatbots for health information and advice. A public opinion poll released in March found that a third of American adults now use them for health information and advice. Online stories have also accumulated: for some patients, AI seems to deliver what the system couldn’t.
Still, he’s not making the case that chatbots replace clinicians. Experts urge caution. and Danielle Bitterman. clinical lead for data science and AI at Mass General Brigham. has told the New York Times in recent months that general-purpose chatbots are frequently wrong and “have not been thoroughly evaluated” for personalized diagnoses.
Christou doesn’t disagree. “It didn’t replace the doctors,” he says. “It helped me ask the right questions.”
For a condition as rare as his—one an oncologist might see once a year—he argues that access to a model trained on a full sweep of medical literature is not the same as a Google search.
That difference mattered near the end of treatment. His final PET scan—used to detect active disease—came back ambiguous. His oncologist began discussing a second line of therapy, potentially radiotherapy, near his heart and lungs.
Christou said it felt alarming.
He responded by digging into the details of what the imaging might be saying. He read that for this specific lymphoma, the false-positive rate on end-of-treatment PET scans is around 60%—a figure that still surprises him. “It’s 2026,” he says. “Sixty percent.”
He fed all three of his PET scans and his MRI into Claude. The model flagged a phenomenon known to clinicians but easy to miss: in patients under 40 recovering from this type of lymphoma, the thymus gland can reactivate after chemotherapy. On imaging, that reactivation can look like active disease.
Given his age and his specific scan characteristics, the model put the probability of that explanation at roughly 90%.
Christou then sought three more opinions. The fourth doctor confirmed it: thymus rebound. There was no active disease. No radiotherapy was needed. He was clear.
The past year didn’t just change his medical outcome—it changed his relationship with work and time. Christou is still sorting through what the treatment meant for his health. how he works. and how he thinks about the future. Before any of this happened. he had already built Keragon. his current company. an AI-powered platform that helps medical practices automate their administrative operations.
But becoming a patient changed how he sees the machine behind care. He watched nurses and doctors buried under tasks with nothing to do with care. He received the same chemotherapy protocol as an 80-year-old woman. he said. and the side effects were managed through a cascading chain of additional drugs—each creating problems of its own. He believes that when people look back on this era of treatment, they will “cringe.”.
Now, he says, he takes Sundays off mostly. He tries to be present—having lunch with friends. spending time at home with his dog. and allowing conversations to be conversations rather than work disguised as downtime. During treatment, a VC friend had told him something he kept replaying: “Be happy now.”.
Christou says that was among the hardest things to do, and yet he eventually learned it mattered.
He also offered to talk to others going through something similar, to share notes and compare experiences. “It’s not happening in 10 years,” he says of what AI can already do for patients willing to use it. “It’s happening today.”
non-Hodgkin’s lymphoma AI in healthcare Claude PET scan thymus rebound Whoop Oura ring biotech startup chemotherapy