Desperate Patients Turn to AI to Solve Medical Mysteries

“Patients with rare diseases often spend five years or more searching for a diagnosis. Now artificial intelligence is helping some get answers faster.

 

Rachel Hinken long wondered why her son, Oliver, seemed to be missing key growth milestones, including speech and walking delays. He consistently tracked between the zero and first percentile for height. At age 10, he wasn't more than 4 feet tall. Doctors said he was fine. He would catch up. Hinken wasn't convinced.

 

Last year, she uploaded Oliver's picture into Face2Gene, an AI-assisted app designed for healthcare professionals that uses facial analysis to flag rare genetic disorders. A strong match came up for Oliver: a type of Trichorhinophalangeal syndrome, or TRPS. The condition can cause bone or joint issues that lead to pain and problems with movement.

 

Genetic testing and clinical consultations confirmed the tool's result, and revealed that Hinken had TRPS, too. "I screamed, I was like, 'Holy crap! We finally have an answer!'" said Hinken, who lives on New York's Long Island.

 

Patients and families are turning to AI to help pinpoint conditions.

 

 AI can be especially adept at flagging potential rare and hard-to-diagnose diseases, which may otherwise go undetected for years because doctors don't often see them.

 

"I have been a little slack-jawed a couple of times by the difference" AI has made in helping to spot uncommon conditions, said Dr. Sarah Diekman, a doctor who specializes in a subset of nervous-system disorders like Postural Orthostatic Tachycardia Syndrome, or POTS. "I've seen patients who've had this for 50 years, and I was the first person to diagnose." Now, she said, patients who identified POTS with the help of AI chatbots are coming to her within months of their first symptoms.

 

Fidji Simo, the former chief executive of Instacart, has been public about her battle with POTS and stepped down from her post as OpenAI's No. 2 executive in July, citing her health. In an interview with The Wall Street Journal, she said she believes today's AI tools would have helped her get a diagnosis, which took roughly nine months, much more quickly.

 

"I was a textbook case, and doctors missed it because they were just so focused on the fact that I had had a rough pregnancy," said Simo, who first started having symptoms after giving birth to her daughter in 2015.

 

She has used ChatGPT to analyze the results of her whole-genome sequencing, gather information on experimental treatments and brainstorm potential tests to discuss with her doctor.

 

Simo, who is still a part-time adviser at OpenAI, founded a new company focused on researching biological drivers of conditions like POTS and matching patients to drugs.

 

Data-center-driven diagnoses can be even more accurate than doctors'. In a study published last year in a JAMA journal, researchers took 90 complex rare-disease cases that had already been solved and tested AI chatbots' abilities to suggest the right diagnosis.

 

The two chatbots got the diagnoses right in 13% and 10% of cases, respectively, compared with 5.6% of cases that doctors had diagnosed through a review of patients' medical records.

 

AI can be especially good at finding patterns, such as links between physical features in medical imaging and words in medical literature or case reports, doctors and researchers said.

 

That can help spot rare diseases, especially in rural or nonspecialty clinics where doctors may be confronting them for the first time, said Dr. Matthew G. Hanna, a breast pathologist who chairs the College of American Pathologists' AI committee.

 

AI may help provide suggestions for them about what types of tests to run, or what potential treatments could help, Hanna added.

 

Yet there are limits, doctors said. Clinical geneticist Dr. Xiao P. Peng, who helped confirm Hinken's family's diagnoses, said the tools still make mistakes and are better at generating possible leads, translating complex medical jargon and compiling research than making diagnoses.

 

"It searches much faster than we can across many more spaces," said Peng, who is director of advanced diagnostics and therapeutics at the New York Center for Rare Diseases. "But for data synthesis, there has to be a manual human role."

 

The broader problem with AI in rare-disease diagnosis is that existing tools are only as good as the data they are trained on, researchers, doctors and nurses said. There are fewer data points, including case records, tissue samples and images, for rare diseases than more common conditions. Those that do exist aren't often well digitized.” [1]

 

1. U.S. News: Desperate Patients Turn to AI to Solve Medical Mysteries. Janin, Alex.  Wall Street Journal, Eastern edition; New York, N.Y.. 17 Aug 2026: A3.