In coming months and years, we'll see AI analytics used to unlock even richer sources of biomarkers. One MIT team has successfully developed an algorithm that can accurately distinguish COVID-19 infections from other illnesses based on the sound of a cough recorded via a cellphone call, for instance. Given the flood of new research being published as health systems around the world grapple with COVID-19, computerized meta-research is also proving vital as we sift through the data to uncover clinically salient biomarkers.
Advanced whole-body imaging, which looks not just at each organ but the body as a whole, is also opening the door to new clinical insights is also opening the door to new clinical insights, with researchers able to rely not just on structural changes in physical organs, but also on functional data showing blood flow, metabolic activity — and, yes, even the accumulation of "sweat" around certain organs. Used in conjunction with machine learning technologies, such approaches can also tease out complex network effects, such as identifying variances in the way that the brain, lungs and legs all interact in patients with cardiovascular disease. These interactions can serve as new biomarkers that can lead to even earlier warnings of an underlying medical condition. Even before symptoms become apparent to patients.
Too much information?
Numed, a well established company in business since 1975 provides a wide range of service options including time & material service, PM only contracts, full service contracts, labor only contracts & system relocation. Call 800 96 Numed for more info.
Are there downsides to all these biomarkers? Well, perhaps in some cases. Over-diagnosis of diseases that are relatively benign can be a real concern: we spot far more early-stage thyroid cancers than we used to, for instance, but because many thyroid tumors are extremely slow-growing, that means we're conducting more thyroidectomies (and shunting more patients into lifelong post-thyroid treatment protocols) without necessarily improving clinical outcomes.
In other cases — as with those COVID-19 prognostic biomarkers — more information can create ethical headaches. Nobody wants to deny patients life-saving treatment based on a blood test or an MRI scan. Still, as long as healthcare professionals are constrained by limited resources, from ICU beds to transplant organs, there will always be an aspect of triage and rationing to the work they do — and if we have to have rationing, it's better for it to be based on data and scientific insights.
The reality is that while healthcare professionals sometimes wind up having to make difficult decisions, there's no such thing as too much information in the medical sphere. Change is always unsettling, but with AI tools on hand to help us make sense of a flood of new data from imaging tools and assays, we're making smarter decisions and delivering better care to our patients. In months and years to come, novel biomarkers will empower us to diagnose illnesses earlier, deliver more targeted and effective care, and unlock powerful new treatments for diseases of all kinds. For both patients and healthcare professionals, that's unequivocally good news.