AI in Health Care: Balancing Benefits and Barriers
AI can help alleviate the burden on clinical labs—but only with sufficient investment, enthusiasm, and understanding
Keep up to date on new and emerging diagnostic tests, testing trends and opportunities, and disruptive technologies
AI can help alleviate the burden on clinical labs—but only with sufficient investment, enthusiasm, and understanding
How do the underlying datasets affect artificial intelligence tools’ performance in the lab—and beyond?
Many artificial intelligence-based medical devices have not undergone clinical validation—but what does this mean for the lab?
Lab scientists using testing equipment too quickly brings up training concerns in discussions at recent ADLM conference
Expansion of use for two assays gives patients the option to self-collect specimens at home and in the clinic, which may help address gaps in screening
With the global cancer burden growing, is a universal germline genomic testing approach the key to more effectively combating the disease?
Recent advances in pharmacogenomic testing—and their role in ensuring safe, effective treatment selection for precision oncology
When it comes to cancer, patients’ greatest fear is diagnostic delays—and they believe digital pathology and AI can reduce those delays
Experts—including those in genetics and device regulation—say the AvertD assay did not predict risks of abuse ‘any better than chance’
In an era when genetic and genomic testing are theoretically affordable and accessible, why do so many patients remain undiagnosed?
How are advances in point-of-care testing altering the genetic testing landscape, and what does this mean for the clinical lab?