As the only company providing a complete imaging AI solution that goes beyond neurological image quantification to support the entire patient care pathway, we’re excited to share our platform and solutions at RSNA 2022!
For the collective dementia community, an earlier diagnosis leads to more appropriate care and, ultimately, better patient outcomes. Read more about how thought leaders and clinicians at AAIC 2022 suggest we can improve dementia diagnosis in this blog post.
The need to demystify AI in radiology applications was one of our key takeaways from ECR 2022. Read about some of the discussions and other themes in this blog post from Peter Ngum, Combinostics Clinical Application Specialist, and Greg Kingston, Combinostics Chief Marketing Officer (CMO).
ASNR22 provided a great opportunity to discuss tools that would help neuroradiologists support their referring clinicians when diagnosing patients with symptoms of dementia. Read key takeaways from Peter Ngum, Combinostics Clinical Application Specialist, and Greg Kingston, Combinostics Chief Marketing Officer (CMO).
AAN 2022 highlighted cutting-edge research in neurology and provided opportunities for networking within the neurology community. Read key takeaways from Peter Ngum, Combinostics Clinical Application Specialist, from advances for traumatic brain injury to the future of AI and neurology.
ACTRIMS 2022 highlighted novel scientific discoveries for multiple sclerosis (MS), with a focus on MS biomarkers. Read key takeaways from Peter Ngum, Combinostics Clinical Application Specialist, from better, novel treatments to the potential of enhanced AI-based neuroimaging for improved patient management.
In the third edition of our “Meet the Team” blog series, we talk to Peter Ngum, one of Combinostics’ Clinical Application Specialists, about his academic and industry experience, what he loves about his role, and some fascinating conferences he’s attended recently.
Early detection and differentiation of dementias: with AI, vast amounts of data are an asset, not a burden
Although detection of and differentiation among the various types of dementia remain challenging for clinicians, technological advances such as artificial intelligence (AI) and machine learning (ML) can help.