Over the past decade, Alpha IT has been actively working on a range of projects – many involving Artificial Intelligence (AI) and Artificial Neural Networks (ANN) – to help advance the quality of care provided by physicians, and improve the efficacy and efficiency of the broader healthcare system.
The company’s research strength is borne out by the fact that we hold two patents and two certified industrial designs (in Canada and internationally); have another five projects at the patent application stage; and are actively exploring several other leading-edge fields of inquiry that will significant enhance disease treatment protocols and everyday clinical practice.
Selected patents and industrial designs
Using advanced mathematics, this technology – patented in Canada, U.S. and by the World Trade Organization – rapidly reviews its integrated repository of medical knowledge and then infers a solution to the issue at hand. The AI system gathers evidence-based data from diverse sources, including Cochrane Reviews, the most recent medical literature, input from practicing specialists and randomized patient records. Unlike other decision-support tools, this system is able to learn from past experiences to improve its future decisions.
In a clinical context, this standalone intelligent system helps physicians arrive at diagnoses more quickly and accurately that using traditional methods. In academic settings, it provides an unequalled knowledge base for use by students and researchers. Finally, it can be added as a standalone software module to Alpha IT’s GlobeMed EMR as an additional expert-knowledge resource.
Alpha IT pioneered the idea of providing space to record clinical encounters alongside a comprehensive view of a patient’s past medical information on a single computer screen. This certified industrial design – registered in Canada and the U.S. – was first implemented on Alpha IT’s earlier UHM EMR software, and is now a key element of its advanced GlobeMed EMR software.
Selected patent-pending and under-review projects
Whether at the scale of an individual practitioner’s office or an entire hospital department, optimizing appointment scheduling holds enormous promise for improving the utilization of precious healthcare resources.
Using optimization science, Alpha IT has made major progress in developing an intelligent system that resolves ongoing scheduling inefficiencies and can rapidly identify the least disruptive changes to address sudden schedule changes due to emergencies. This research is currently at the ‘patent-pending’ stage in Canada and the U.S.
One of the most significant challenges in contemporary healthcare is wait-times for medical procedures. While conventional wisdom holds that more money is required to solve the issue, Alpha IT’s research is identifying alternative remedies.
In many cases, medical wait-times are exacerbated by one or more bottlenecks or inefficiently used resources in an overall process. Alpha IT’s research modeling, which relies on sophisticated mathematical algorithms and queuing theory, has achieved dramatic wait-time reductions through intelligent scheduling practices or selectively implementing additional resources. The fruits of this vital research (for which patents are pending in Canada and the U.S.) will soon help address this pressing healthcare priority.
Today’s healthcare system is bursting with valuable medical data, yet much of this data is unusable in its current form. Some is trapped as unstructured text in digital records that cannot be grouped and sorted, while other data is plagued by spelling mistakes that prevent automatic sorting.
Leveraging Artificial Intelligence and statistical modeling, Alpha IT is developing ways to sift through vast quantities of data and extract actionable insights that can advance the progress of evidence-based medicine. This research is at the ‘patent-pending’ stage in the U.S.
Other areas of current research
Here is a summary of several of the company’s future research goals:
- Transforming the way images of cancer tumours are understood and classified (resulting in more accurate interpretation, disease diagnosis and treatment).
- Enabling practitioners to more efficiently capture and document their clinical observations (helping achieve true interoperability among different software systems).
- Unlocking medical information previously trapped in handwritten notes (further enriching the impact of evidence-based medicine).
- Improving the accuracy of cancer incidence and mortality forecasting (enabling policymakers to allocate scarce resources more effectively).