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
Emerging Tests-dtet
Dissecting the Data Behind Healthcare AI
How do the underlying datasets affect artificial intelligence tools’ performance in the lab—and beyond?
Has Your AI Been Validated?
Many artificial intelligence-based medical devices have not undergone clinical validation—but what does this mean for the lab?
Profiling Pathogens for Public Health
Genomic epidemiology can provide insights into pathogen transmission and evolution—and facilitate better countermeasures against infectious disease.
Expert Q&A: Key Developments in AI and Digital Pathology
Juan Antonio Retamero, MD, shares his thoughts on recent trends in AI and digital pathology, and how they may progress.
Seeing Past the AI Hype
Artificial intelligence won’t take your job—but what are the real concerns around healthcare AI and its use?
AI: The Newest Member of the Lab Team?
AI is an increasingly useful tool in pathology—but its full value can only be realized in collaboration with human experts.
Which Test? Choosing the Best Approach to Diagnosing Rare Disease
Genomic sequencing is almost twice as likely to yield a diagnostic result, but lags behind panel testing in speed, cost, and concordance.
Addressing the Challenges of Bile Acid Diarrhea Diagnosis
A new five-metabolite blood test designed by algorithm could simplify and speed up this challenging diagnosis.
Can Ophthalmic Biomarkers Offer Insights into Brain Pathologies?
Protein levels in the vitreous humor may have the potential to support the diagnosis and staging of neurodegenerative diseases.
New Blood-Based PTSD Biomarkers Revealed
A simple blood test may help screen, identify, intervene, treat, monitor, and eventually, prevent PTSD.
New Device Predicts the Efficacy of Hypnosis Treatment for Pain
The inexpensive POC device is a biosensor that performs COMT genotyping as a biomarker for hypnotizability.
Simplifying Antidepressant Quantification in Clinical Labs
A recent study provides insights on how to use automation and only 20 μL of a serum sample to quantify blood levels of antidepressants.
