FGAI4H-F-012-A01-R1 Zanzibar, 3-5 September 2019
Description: FGAI4H-F-012-A01-R1 Zanzibar, 3-5 September 2019 Meeting F Topic Group Update Ophthalmology (TG-Ophthalmo ) Zanzibar, Sep 3 5, 2019 Arun Shroff, Topic Driver, TG-Ophthalmology Topic Group Ophthalmology Topics in this group: Diabetic
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slide1. FGAI4H-F-012-A01-R1 Zanzibar, 3-5 September 2019<br>
slide2. Meeting F Topic Group Update Ophthalmology (TG-Ophthalmo ) Zanzibar, Sep 3 – 5, 2019
Arun Shroff, Topic Driver, TG-Ophthalmology<br>
slide3. Topic Group – Ophthalmology Topics in this group:
Diabetic Retinopathy (DR)
Age Related Macular Degeneration (AMD)
Glaucoma (GC)
Pathological Myopia (PM)
Topic Group Description Document (FGAI4H-F-012)
Topic Group Call for Participation (FGAI4H-F-005-A07)<br>
slide4. The Health Challenge Diabetic Retinopathy (DR)
At risk population - 422M people with diabetes worldwide (2014)
35%, 148M have DR / 11%, 48M have Vision Threatening DR (64M by 2040)
Leading cause of blindness among adults worldwide
Age Related Macular Degeneration (AMD)
Damages macula and impairs central vision
196M by 2020
Third leading cause of vision loss overall, leading cause for those over 50<br>
slide5. The Health Challenge Glaucoma (GC)
Damages optic nerve & leads to vision loss
80M by 2020
Pathological Myopia (PM)
Global Prevalence is 0.9% to 3.1%
35% of people with myopia have High Myopia, which can develop into PM
Need for AI: Acute shortage of specialists globally to screen everyone at risk – specially in LMICs.<br>
slide6. Benchmarking: DR Classifications Multi-class Classification:
[0 (Nongradable Image) ]
1(No DR)
2 (Mild)
3 (Moderate NPDR)
4 (Severe NPDR)
5 (PDR)
Binary :
[0 (Nogradable Image)]
1 (Nonreferable Retinopathy = No DR or Mild)
2 (Referable Retinopathy = Moderate, Severe, PDR)<br>
slide7. Benchmarking: AMD, GC, PM Classifications AMD:
[0 (Image Nongradable)]
1 (No/early stage AMD
2 (Intermediate/advanced stage AMD)
GC:
[0 (Image Nongradable.]
1 (No GC)
2 (GC)
PM:
[0 (Image Nongradable)]
1 (No PM/HM)
2 (HM: high myopia)
3 (PM)<br>
slide8. Available Public Datasets - DR EyePACS dataset:
Approx 90,000 fundus images, 5 levels of severity
Kaggle: (derived from EyePACS)
Approx 35,000 images : 5 levels of severity
MESSIDOR dataset:
1,200 images, 4 levels of severity
DiaRetDB dataset:
~ 200 images marked with lesions etc<br>
slide9. Available Public Datasets - AMD, GC AMD:
AREDS dataset:
(AgeRelated Eye Disease Study )
Images from ~4700 patients :
KORA dataset: (Cooperative Health Research in the Region of Augsburg (KORA) dataset,)
Approx 2840 patient records
GC:
ORIGA, 650 fundus images
Retinal fundus images for glaucoma analysis (RIGA, 760 images)
ACHIKO-K (258 images)
DRISHTI-GS (100 images)<br>
slide10. Benchmarking Metrics Sensitivity:
% of positive (disease) cases correctly classified
True Positive/(True Positive + False Negative)
Specificity:
% of negative (normal) cases correctly classified
True Negative/(True Negative + False Positive)
AUC (Area Under ROC);
Sensitivity Vs (1-Specificity) plotted at different points of the model
Other Metrics: Precision/Accuracy, F1 Score, Confusion Matrix<br>
slide11. Use-Case & Topic Group History Meeting B - New York, 15-16 November 2018
AI for Ophthalmology Use case submitted in response to the Call for Proposals
“Using AI for Early Detection of DR to Prevent Vision Loss” accepted as a use case
Meeting C - Lausanne, Switzerland, 22-25 January 2019
Status report on the use case “Using AI for Early Detection of DR”
Topic Group “Ophthalmology” established
2 Members :
Medindia.net / Xtend.ai
Baidu, China.<br>
slide12. Use-Case & Topic Group History Meeting D- Shanghai, April 2-5, 2019
Topic Description Document (TDD) – Version 1 completed
Topic Group Status Update
Meeting E - Geneva, May 30 – June 1, 2019
Topic Description Document (TDD) Updated
Edits / Corrections made
Pathological Myopia (PM) added (by Xingxing Cao, Baidu)
Reviewed and validated by topic group members
New topic group members:
Ashley Kras, M.D. M. S., Ophthalmologist & Bioinformatician<br>
slide13. Progress Since Meeting E Call For Participation:
Outreach via email / social media
Several inbound emails with interest in joining/contributing to group
New Topic group members:
Dr Covadonga Bascaran, PHEC MSc Programme Director, International Centre for Eye Health (ICEH), London School of Hygiene & Tropical Medicine
Inês Sousa , Head of Intelligent Systems, Fraunhofer Portugal
Online Meetings/Calls:
Prof Leo Celi, Clinical Research Director, Harvard MIT Division of Health Science and Technology and Ash Krasley: (June 22, 2019)
Details about MIT Open Access Project
Potential collaboration with FGAI4H / Contribution of Data
Dr. Jorge Cuadros, EyePACS (July 22, 2019)
Database of over 5 million images
Discussion about contributing datasets (ongoing)<br>
slide14. Progress Since Meeting E Online Meetings/Calls:
Topic Group Meeting, (Jul 31, 2019):
Participants: Dr. Covadonga Bascaran & Inês Sousa
Discussion about DR-Net
Possibility of getting undisclosed data sets for testing
Contribution of data from different countries to make data representative
Images are not currently annotated/labeled – this would need to be done
Other meetings/projects:
Meeting in Geneva with ITU/WHO, Sanofi, Aivision.health(France), Minister of Health, Senegal
Discussion about pilot project in Senegal - AI for DR detection, target start date Nov 2019<br>
slide15. Topic Group – Ophthalmology Members Arun Shroff, Xtend.AI and Medindia.net
Topic Driver for TG-Ophthalmology
Yanwu XU, Artificial Intelligence Innovation Business, Chief Scientist, Baidu, China
Xingxing Cao, Artificial Intelligence Group, Baidu, China
Jingyu WANG, Artificial Intelligence Group, Baidu, China
Shan Xu, CAICT, China
Ashley Kras, M.D. M. S., Ophthalmologist & Bioinformatician (Harvard Medical School)
Covadonga Bascaran, PHEC MSc Programme Director, International Centre for Eye Health (ICEH), London School of Hygiene & Tropical Medicine, U.K.
Inês Sousa, Head of Intelligent Systems, Fraunhofer Portugal AICOS<br>
slide16. Next Steps Topic Description Document
Continue to improve TDD for accuracy and completeness
TDD validation from experts
Call For Participation
Continue outreach to increase members and get more experts involved
Datasets/Benchmarking:
Follow-up with DR-Net, EyePACs, Moorefields, Open Eye & others for
collaboration and procurement of undisclosed, labeled datasets for benchmarking.
Start working on benchmarking process & protocols.<br>
slide17. Thank you!<br>
slide2. Meeting F Topic Group Update Ophthalmology (TG-Ophthalmo ) Zanzibar, Sep 3 – 5, 2019
Arun Shroff, Topic Driver, TG-Ophthalmology<br>
slide3. Topic Group – Ophthalmology Topics in this group:
Diabetic Retinopathy (DR)
Age Related Macular Degeneration (AMD)
Glaucoma (GC)
Pathological Myopia (PM)
Topic Group Description Document (FGAI4H-F-012)
Topic Group Call for Participation (FGAI4H-F-005-A07)<br>
slide4. The Health Challenge Diabetic Retinopathy (DR)
At risk population - 422M people with diabetes worldwide (2014)
35%, 148M have DR / 11%, 48M have Vision Threatening DR (64M by 2040)
Leading cause of blindness among adults worldwide
Age Related Macular Degeneration (AMD)
Damages macula and impairs central vision
196M by 2020
Third leading cause of vision loss overall, leading cause for those over 50<br>
slide5. The Health Challenge Glaucoma (GC)
Damages optic nerve & leads to vision loss
80M by 2020
Pathological Myopia (PM)
Global Prevalence is 0.9% to 3.1%
35% of people with myopia have High Myopia, which can develop into PM
Need for AI: Acute shortage of specialists globally to screen everyone at risk – specially in LMICs.<br>
slide6. Benchmarking: DR Classifications Multi-class Classification:
[0 (Nongradable Image) ]
1(No DR)
2 (Mild)
3 (Moderate NPDR)
4 (Severe NPDR)
5 (PDR)
Binary :
[0 (Nogradable Image)]
1 (Nonreferable Retinopathy = No DR or Mild)
2 (Referable Retinopathy = Moderate, Severe, PDR)<br>
slide7. Benchmarking: AMD, GC, PM Classifications AMD:
[0 (Image Nongradable)]
1 (No/early stage AMD
2 (Intermediate/advanced stage AMD)
GC:
[0 (Image Nongradable.]
1 (No GC)
2 (GC)
PM:
[0 (Image Nongradable)]
1 (No PM/HM)
2 (HM: high myopia)
3 (PM)<br>
slide8. Available Public Datasets - DR EyePACS dataset:
Approx 90,000 fundus images, 5 levels of severity
Kaggle: (derived from EyePACS)
Approx 35,000 images : 5 levels of severity
MESSIDOR dataset:
1,200 images, 4 levels of severity
DiaRetDB dataset:
~ 200 images marked with lesions etc<br>
slide9. Available Public Datasets - AMD, GC AMD:
AREDS dataset:
(AgeRelated Eye Disease Study )
Images from ~4700 patients :
KORA dataset: (Cooperative Health Research in the Region of Augsburg (KORA) dataset,)
Approx 2840 patient records
GC:
ORIGA, 650 fundus images
Retinal fundus images for glaucoma analysis (RIGA, 760 images)
ACHIKO-K (258 images)
DRISHTI-GS (100 images)<br>
slide10. Benchmarking Metrics Sensitivity:
% of positive (disease) cases correctly classified
True Positive/(True Positive + False Negative)
Specificity:
% of negative (normal) cases correctly classified
True Negative/(True Negative + False Positive)
AUC (Area Under ROC);
Sensitivity Vs (1-Specificity) plotted at different points of the model
Other Metrics: Precision/Accuracy, F1 Score, Confusion Matrix<br>
slide11. Use-Case & Topic Group History Meeting B - New York, 15-16 November 2018
AI for Ophthalmology Use case submitted in response to the Call for Proposals
“Using AI for Early Detection of DR to Prevent Vision Loss” accepted as a use case
Meeting C - Lausanne, Switzerland, 22-25 January 2019
Status report on the use case “Using AI for Early Detection of DR”
Topic Group “Ophthalmology” established
2 Members :
Medindia.net / Xtend.ai
Baidu, China.<br>
slide12. Use-Case & Topic Group History Meeting D- Shanghai, April 2-5, 2019
Topic Description Document (TDD) – Version 1 completed
Topic Group Status Update
Meeting E - Geneva, May 30 – June 1, 2019
Topic Description Document (TDD) Updated
Edits / Corrections made
Pathological Myopia (PM) added (by Xingxing Cao, Baidu)
Reviewed and validated by topic group members
New topic group members:
Ashley Kras, M.D. M. S., Ophthalmologist & Bioinformatician<br>
slide13. Progress Since Meeting E Call For Participation:
Outreach via email / social media
Several inbound emails with interest in joining/contributing to group
New Topic group members:
Dr Covadonga Bascaran, PHEC MSc Programme Director, International Centre for Eye Health (ICEH), London School of Hygiene & Tropical Medicine
Inês Sousa , Head of Intelligent Systems, Fraunhofer Portugal
Online Meetings/Calls:
Prof Leo Celi, Clinical Research Director, Harvard MIT Division of Health Science and Technology and Ash Krasley: (June 22, 2019)
Details about MIT Open Access Project
Potential collaboration with FGAI4H / Contribution of Data
Dr. Jorge Cuadros, EyePACS (July 22, 2019)
Database of over 5 million images
Discussion about contributing datasets (ongoing)<br>
slide14. Progress Since Meeting E Online Meetings/Calls:
Topic Group Meeting, (Jul 31, 2019):
Participants: Dr. Covadonga Bascaran & Inês Sousa
Discussion about DR-Net
Possibility of getting undisclosed data sets for testing
Contribution of data from different countries to make data representative
Images are not currently annotated/labeled – this would need to be done
Other meetings/projects:
Meeting in Geneva with ITU/WHO, Sanofi, Aivision.health(France), Minister of Health, Senegal
Discussion about pilot project in Senegal - AI for DR detection, target start date Nov 2019<br>
slide15. Topic Group – Ophthalmology Members Arun Shroff, Xtend.AI and Medindia.net
Topic Driver for TG-Ophthalmology
Yanwu XU, Artificial Intelligence Innovation Business, Chief Scientist, Baidu, China
Xingxing Cao, Artificial Intelligence Group, Baidu, China
Jingyu WANG, Artificial Intelligence Group, Baidu, China
Shan Xu, CAICT, China
Ashley Kras, M.D. M. S., Ophthalmologist & Bioinformatician (Harvard Medical School)
Covadonga Bascaran, PHEC MSc Programme Director, International Centre for Eye Health (ICEH), London School of Hygiene & Tropical Medicine, U.K.
Inês Sousa, Head of Intelligent Systems, Fraunhofer Portugal AICOS<br>
slide16. Next Steps Topic Description Document
Continue to improve TDD for accuracy and completeness
TDD validation from experts
Call For Participation
Continue outreach to increase members and get more experts involved
Datasets/Benchmarking:
Follow-up with DR-Net, EyePACs, Moorefields, Open Eye & others for
collaboration and procurement of undisclosed, labeled datasets for benchmarking.
Start working on benchmarking process & protocols.<br>
slide17. Thank you!<br>