Application of Artificial Intelligence to Pathology Labs

Artificial Intelligence is finally maturing and finding applications in all aspects of our lives including in autonomous driving, cancer cell detection, and intelligent home devices. The amount of data being generated, gathered, analyzed, and mined has successfully resulted in meaningful automated actions in all industries.

Doctors and researchers using innovative technologies for medicine and healthcare: artificial intelligence, virtual reality, drones, stem cells and digital organs

Reduction in the cost of data storage devices, easy accessibility of the cloud-based data stores through fast Internet connections and with the ever-increasing compute power, unimaginable 30+ years ago has certainly fueled the widespread use of data-based decisionmaking . This has been instrumental in making the machines become helpful aids in validating the experiential art of drawing conclusions. Large amounts of operational data is being generated by the Pathology labs.  This data, if captured and made available in a meaningful manner, will ultimately offer useful and actionable insights into all aspects of the lab business from client acquisition, case volume growth, and cost reduction, and diagnoses.

As for specific examples for an Anatomic Pathology lab, a software application like SpeedsPath AP and Molecular Lab Information System comes well-equipped to capture the day-to-day data from ordering, lab processing to reporting. But the raw data does not by itself provide any insight without the use of sophisticated reports, dashboards and key performance indicators.  While no lab system can offer all the data analysis leading to automated decisionmaking, being able to export the data and feeding it into the AI tools may lead ultimately to drawing logical conclusions which will approach the ability of lab professionals. It behooves me to state here that the historical data is often a good indicator of the trends but may not always lead to correct predictions. This is where one needs to apply imagination to predict the future needs and not be totally dependent on the history. An oft-used analogy comes to mind here about driving a car with always looking through the rear-view mirror and camera.

In conclusion, AI will continue to find inroads into all aspects of Pathology Lab operations with innovations into instruments, devices, data gathering, and analysis. In subsequent blogs we will touch on the benefits of barcoding, slide scanning, and Digital Pathology techniques as exploited in our SpeedsPath system.