How to Better Harmonize Lab Test Results
Unharmonized and unstandardized test results can affect patient care. Here are steps that clinical labs can take to resolve this problem
Testing Trends-dtet
Diagnostics Pipeline: FDA Approves Visby Medical’s Over-The-Counter Women’s Sexual Health Test
It’s the first PCR-based sexually transmitted infection test platform for at-home use
Experts Discuss Opportunities and Challenges for NGS
Next-generation sequencing is reshaping how labs detect, understand, and manage disease
A Lasting Impact: COVID-19 and Cancer Screening
Several years after the onset of the COVID-19 pandemic, labs are still dealing with the effects of missed and delayed screenings
Lab Data’s New Role as the Backbone of AI-Driven Clinical Trials
Learn how research and development labs can leverage AI to transform laboratory data into actionable insights
Generalizing Genomics Learning
A new NIH network aims to remove barriers and share knowledge to drive more widespread adoption of genomics in clinical settings
AI in Genomics: The Next Generation
How artificial intelligence and machine learning tools stand to benefit clinical labs throughout the genomics pathway
When Is Genome Sequencing Advisable?
With patient and provider demand for WGS on the rise, what should laboratorians know about ordering and interpreting this testing?
Computing the Future of the Lab
Computational biology expert Keaun Amani shares his advice and insights on AI and machine learning tools for the clinical lab
Dissecting the Data Behind Healthcare AI
How do the underlying datasets affect artificial intelligence tools’ performance in the lab—and beyond?
PGx Testing: First, Do No Harm
Recent advances in pharmacogenomic testing—and their role in ensuring safe, effective treatment selection for precision oncology
The Demand for Digital Pathology
When it comes to cancer, patients’ greatest fear is diagnostic delays—and they believe digital pathology and AI can reduce those delays
Syndromes Without a Name Bring Labs an Uphill Battle
In an era when genetic and genomic testing are theoretically affordable and accessible, why do so many patients remain undiagnosed?
