Augmented vs Artificial Intelligence for Stratification of Patients with Myositis

Augmented vs Artificial Intelligence for Stratification of Patients with Myositis

Just published ‘Augmented versus Artificial Intelligence for Stratification of Patients with Myositis‘, the correspondence in BMJ Annals of Rheumatic Diseases, discussing the potential of Machine Learning, AI and Big Data to improve the stratification of patients, especially when the available data is limited.

We believe that AI driven approaches are a powerful alternative to human judgement and can improve future classification criteria, especially for patients with rare diseases or when it comes to the analysis of datasets from small cohorts. We also believe that today complimenting a human with the machine is more powerful than replacing a human judgement all together,  thus relying on augmented judgement when making the final decision on patient stratification especially when building AI-based models.

Authors: Michael MahlerBrenden RossinOlga Kubassova

Read more:

1. Pinal-Fernandez I, Mammen AL, On using machine learning algorithms to define clinically meaningful patient subgroups. Ann Rheum Dis2019. doi:

doi:10.1136/annrheumdis-2019-215852.

2. Spielmann L, Nespola B, Séverac F, et al, Anti-Ku syndrome with elevated CK and anti-Ku syndrome with anti-dsDNA are two distinct entities with different outcomes. Ann Rheum Dis2019;78:1101–6.

doi:10.1136/annrheumdis-2018-214439

3. Mariampillai K, Granger B, Amelin D, et al, Development of a new classification system for idiopathic inflammatory myopathies based on clinical manifestations and myositis-specific autoantibodies. JAMA Neurol2018;75:1528.

doi:10.1001/jamaneurol.2018.2598 

4. Vulsteke J-B, De Langhe E, Mahler M, Autoantibodies at the Center of (sub)Classification—Issues of Detection. JAMA Neurol2019;76:867. 

doi:10.1001/jamaneurol.2019.0440

5. Gossec L, Kedra J, Servy H, et al, EULAR points to consider for the use of big data in rheumatic and musculoskeletal diseases. Ann Rheum Dis2019. doi:

doi:10.1136/annrheumdis-2019-215694

6. Lilleker JB, Vencovsky J, Wang G, et al, The EuroMyositis registry: an international collaborative tool to facilitate myositis research. Ann Rheum Dis2018;77:30–9. 

doi:10.1136/annrheumdis-2017-211868 

7. Lundberg IE, Bottai M, Tjärnlund A Response to: ‘Performance of the 2017 European League Against Rheumatism/American College of Rheumatology classification criteria for adult and juvenile idiopathic inflammatory myopathies in clinical practice’ by Hočevar et al. Ann Rheum Dis2018;77:e91. 

doi:10.1136/annrheumdis-2017-212786 

8. Malaviya AN, 2017 EULAR/ACR classification criteria for adult and juvenile idiopathic inflammatory myopathies and their major subgroups: little emphasis on autoantibodies, why?Ann Rheum Dis2018;77:e77. 

doi:10.1136/annrheumdis-2017-212701

About IAG

IAG, Image Analysis Group is a unique clinical development partner to life sciences companies. We broadly leverage our proprietary image analysis methodologies, power of our cloud platform DYNAMIKA, years of experience in AI and Machine Learning as well as bespoke co-development business models to ensure higher probability for promising therapeutics to reach the patients. Our independent Bio-Partnering division fuses risk-sharing business models and agile culture to accelerate novel drug development, www.ia-grp.com

About Inova Diagnostics, the Werfen Company

We’re a global market leader in autoimmune diagnostics, delivering highly accurate reagents and highly efficient automation to labs throughout the world. https://www.inovadx.com/about-us

News
Events