Painting a better picture of health: From faster delivery times to more accurate diagnoses, AI-powered medical imaging is revolutionising the future of our global healthcare system [Advertorial]
#Machinelearning brings an early diagnostic for #pancreaticcancer a step closer to reality @lshtmpress @PLOSONE https://medicalxpress.com/news/2021-06-machine-early-diagnostic-pancreatic-cancer.html
Diagnostic AI algorithm focuses on privacy protection – Physics World - Medical Physics Web https://physicsworld.com/a/diagnostic-ai-algorithm-focuses-on-privacy-protection/ via @GoogleNews #AI #Algorithms #ArtificialIntelligence #DataScience @SpirosMargaris @andi_staub @nigewillson @gerald_bader @Nicochan33
TOMORROW: Join me at @cnbc's #HealthyReturns Summit for a fascinating discussion of how medical algorithms, digital diagnostic & clinical tools can be used by health care pros to provide better treatments. Register now! http://cnbcevents.com/healthyreturns #BigData @cnbcevents https://t.co/Kl0UHoVvPC
Engineers at @DukeU used #machinelearning to develop a #microscope capable of teaching itself the optimal settings needed to complete a diagnostic task: http://bit.ly/36mtZZM via @PhotonicsMedia #medicaldiagnostics #microscopy #optics #biophotonics https://t.co/OzkJOujdYD
INCREDIBLE. Genomics solves a medical mystery dating all the way back to 1968! -An extremely long "diagnostic odyssey" ended thanks to modern DNA science https://uchicagomedicine.org/forefront/gastrointestinal-articles/2019/october/gene-discovery-solves-51-year-old-mystery-cause-of-inherited-pancreatitis #SciComm #SNRTG #MedEd #technology #genomics #genetics #RareDisease #OpenScience #STEM #BigData #IoT https://t.co/MPzcy0YtWD
#MedicalImaging is a main diagnostic tool. #UAlberta spinoff @Medo_ai has disruptive #HealthTech - 3D #ultrasound app + #AI - that enables expert analysis of medical images anywhere. #FallingWalls19 #ABbiz #MachineLearning @TECEdmonton @StartupEdmonton https://t.co/wAVRVhYHMi
The great irony of #MachineLearning for medical applications: On one hand, everything is "data-driven", "makes no assumptions" etc. On the other, diagnostic labels are taken as ground truth.