The medical field is undergoing transformation with the advent of artificial intelligence. It enables the early detection of diseases like ovarian cancer and hastens the diagnosis of infections. Such innovative use of AI unlocks patterns in blood tests that were too complex for humans to interpret and offers hope for more accurate and timely treatments.
Early Detection of Ovarian Cancer
The much talked about ovarian cancer – one that is termed to be “rare, underfunded, and deadly,” is notoriously hard to spot early. Usually beginning in the fallopian tubes and typically having already spread before symptoms materialize, a new line of AI-powered blood tests promise to identify early warning signs years before symptoms appear.
The biomedical engineer, Dr. Daniel Heller, is at the helm of this research at Memorial Sloan Kettering Cancer Center. His team employs carbon nanotubes-thin, light-emitting structures-to detect minute molecular patterns in blood samples. Such patterns are impossible to be seen with the naked eye and decoded through machine learning algorithms. Initial results have shown that AI can perform better than conventional cancer biomarkers, even when training data is minimal.
“This technology could one day help triage gynaecological diseases, providing doctors with tools to quickly differentiate between cancer and other conditions,” says Dr. Heller. He estimates this breakthrough could be available within five years.
AI Speeds Up Diagnosis of Deadly Infections
Beyond cancer detection, AI is changing the speed and accuracy with which infectious diseases are diagnosed. For pneumonia—the sometimes lethal complication of infections in cancer patients—California-based Karius has devised an AI-driven blood test that identifies the precise pathogen causing the infection within 24 hours.
Traditionally, diagnosing pneumonia requires some 20 separate tests a week, costing about $20,000. The test developed by Karius just compares microbial DNA in samples of blood to a big database of tens of billions of data points, pinpointing the exact pathogen to guide treatment with the correct antibiotic.
“Without AI this level of precision and speed wouldn’t be possible,” points out Karius CEO Alec Ford.
Overcoming Obstacles in AI-Driven Diagnostics
While the potential of AI in blood testing is immense, challenges remain. One of the biggest hurdles is the unavailability of high-quality training data. Rare diseases such as ovarian cancer lack a large dataset, and issues of privacy often prevent hospitals from sharing patient data.
To address this issue, organizations such as the Ovarian Cancer Research Alliance are funding large-scale patient registries. These registries allow researchers access to electronic medical records for algorithm training.
“We’re still in the early days of AI in medicine,” says Audra Moran, head of the Alliance. “It’s like the wild west, but the possibilities are extraordinary.”
A Future of AI-Enhanced Healthcare
From early cancer detection to faster infection diagnosis, AI is transforming how it is done and interpreted concerning blood tests. With each day of data and advancement sensors, the medical world pushes closer to a time in which life-threatening conditions can be identified and consequently treated with unprecedented speed and accuracy.
