Top Tweets for #IFMachineLearning
PHG Foundation's Alison Hall chairing the panel at last night's #MachineLearning in Healthcare conference from @IF_Cambridge #IFMachineLearning https://t.co/WPVaKclJOa
What is the single biggest data challenge? - Alison Hall @PHGFoundation Access to high quality data @MSFTResearchCam , negative data @benevolent_ai @benevolent_bio, data dynamism and access AI VIVO #IFMachineLearning #panel #KickOff
Impressive talk by Antonio Criminisi from @MSFTResearchCam featuring #deepforests in action, and a great panel discussion on #MachineLearning in healthcare. Perfect ending of a visit to Alma Mater @ChemCambridge #IFMachineLearning
#IFMachineLearning Want to talk more about machine learning? Join the networking activities after the talks @IF_Cambridge @Innovation_F
Unified protocols for dealing with patient consent and public education regarding benefits of consented data - Antonio Criminisi @MSFTResearchCam @IF_Cambridge #IFMachineLearning
Identifying disease by their underlying molecular signature which overlap significantly across diseases- Jamie Domingues @benevolent_ai @IF_Cambridge #IFMachineLearning
Standardised metrics to compare publicly available to privately accessed (commercial) data - Peyman Gifani #AIVIVO #IFMachineLearning @Innovation_F
Effective communication between companies, patients and the public to build trust and confidence in data usage and ML-backed insights - Insights from panel discussion at @IF_Cambridge #IFMachineLearning event @benevolent_ai @PHGFoundation @MSFTResearchCam @Innovation_F
Consent is a big issue when it comes to use of patient data for ML applications. There needs to be a unified protocol for making patients aware how their data will be used, by who and for what purpose. - Antonio Criminisi. #IFMachineLearning
Q2. If you could change one metric/standard/regulation what would it be ? -Alison Hall @PHGFoundation @IF_Cambridge #IFMachineLearning with @lymphidaki @Dr_SrishtiGupta @CSamarghitean
Access to high quality data which accurately represent dynamics in diseases is important - Insights from panel discussion @IF_Cambridge #IFMachineLearning event @Innovation_F @MSFTResearchCam @benevolent_ai @PHGFoundation
What is the single biggest data challenge? - Alison Hall @PHGFoundation Access to high quality data @MSFTResearchCam , negative data @benevolent_ai @benevolent_bio, data dynamism and access AI VIVO #IFMachineLearning #panel #KickOff
@benevolent_ai pushing the boundaries of known biological targets and chemical space @IF_Cambridge @Innovation_F #IFMachineLearning
Great to attend the Innovation Forum: Machine Learning in Healthcare event this evening sponsored by TTP. @ttp_plc @IF_Cambridge @Innovation_F #IFMachineLearning #machinelearning #healthcare #AI
AI VIVO: innovative data-driven prediction pipeline for exploring new biological questions, disease modulation tools, and drug development #AIVIVO #IFMachineLearning @IF_Cambridge @Innovation_F
Dr Peyman Gifani from #AIVIVO: Machine Learning is important for probing unexplored chemical space and disease areas @IF_Cambridge #IFMachineLearning @Innovation_F
Attending @IF_Cambridge event on #IFMachineLearning, full room & very interesting talk on using #AI for processing images for radiology https://t.co/4tpjDxgQig
First up: Antonio Criminisi @MSFTResearchCam @MSFTResearch talking about the power of #MachineLeaning learning in the context of the analysis of #radiology images #IFMachineLearning @Innovation_F
The prospect of adaptive radiotherapy could be implemented in hospitals in the future improving quality of therapy. Better, automated tracking and more cost efficient therapy planning using machine learing algorithms for better #healthcare. #IFMachineLearning
Live demonstration of @MSFTResearchCam Project InnerEye by Dr Antonio Criminisi at @IF_Cambridge #IFMachineLearning event @Innovation_F
Using deep decision trees for semantic segmentation of CT scans; Dr. Antonio Criminisi @MSFTResearchCam #IFMachineLearning @IF_Cambridge
Excited to hear Antonio Criminisi of @MSFTResearchCam speak about Inner Eye used for analysis of radiology images. #IFMachineLearning
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