DEDector: Smartphone-Based Noninvasive Screening of Dry Eye Disease
Authors: 
Vaibhav Ganatra, Soumyasis Gun, Pallavi Joshi, Anand Balasubramaniam, Kaushik Murali, Nipun Kwatra, 
Mohit JainAuthors Info & Claims
Vaibhav Ganatra, Soumyasis Gun, Pallavi Joshi, Anand Balasubramaniam, Kaushik Murali, Nipun Kwatra, Mohit JainAuthors Info & ClaimsArticle No.: 190, Pages 1 - 26
Abstract
Dry Eye Disease (DED) is an eye condition characterized by abnormalities in tear film stability. Despite its high prevalence, screening for DED remains challenging, primarily due to the invasive nature of most diagnostic tests. The Fluorescein Break-Up Time (FBUT) test, which involves instilling fluorescein dye in the eye, is a widely used method for assessing tear film stability. In this work, we propose DEDector, a low-cost, smartphone-based automated Non-Invasive Break-Up Time (NIBUT) measurement for DED screening. Utilizing a 3D-printed Placido ring attachment on a smartphone's camera, DEDector projects concentric rings onto the cornea, capturing a video for subsequent analysis using our proposed video processing pipeline to identify tear film stability. We conducted a real-world evaluation on 46 eyes, comparing DEDector with the traditional FBUT method. DEDector achieved a sensitivity of 77.78% and specificity of 82.14%, outperforming FBUT.
References
[1]
Filippo Attivissimo, Vito Ivano D'Alessandro, Attilio Di Nisio, Giuliano Scarcelli, Justin Schumacher, and Anna Maria Lucia Lanzolla. 2023. Performance evaluation of image processing algorithms for eye blinking detection. Measurement 223 (2023), 113767. https://doi.org/10.1016/j.measurement.2023.113767
[2]
Robert E. Berger and Stanley Corrsin. 1974. A surface tension gradient mechanism for driving the pre-corneal tear film after a blink. Journal of Biomechanics 7, 3 (1974), 225--238. https://doi.org/10.1016/0021-9290(74)90013-X
[3]
G. Bradski. 2000. The OpenCV Library. Dr. Dobb's Journal of Software Tools (2000).
[4]
Justin Chan, Sharat Raju, Rajalakshmi Nandakumar, Randall Bly, and Shyamnath Gollakota. 2019. Detecting middle ear fluid using smartphones. Sci. Transl. Med. 11, 492 (May 2019), eaav1102.
[5]
Jaykaran Charan and Tamoghna Biswas. 2013. How to calculate sample size for different study designs in medical research? Indian J. Psychol. Med. 35, 2 (April 2013), 121--126.
[6]
Christina Chu, Mark Rosenfield, and Joan Portello. 2014. Blink Patterns: Reading from a Computer Screen Versus Hard Copy. Optometry and vision science: official publication of the American Academy of Optometry 91 (01 2014). https://doi.org/10.1097/OPX.0000000000000157
[7]
Jennifer P Craig, Kelly K Nichols, Esen K Akpek, Barbara Caffery, Harminder S Dua, Choun-Ki Joo, Zuguo Liu, J Daniel Nelson, Jason J Nichols, Kazuo Tsubota, and Fiona Stapleton. 2017. TFOS DEWS II definition and classification report. Ocul. Surf. 15, 3 (July 2017), 276--283.
[8]
Lukasz Cwiklik. 2016. Tear film lipid layer: A molecular level view. Biochimica et Biophysica Acta (BBA) - Biomembranes 1858, 10 (2016), 2421 - 2430. https://doi.org/10.1016/j.bbamem.2016.02.020
[9]
Artem Dementyev and Christian Holz. 2017. DualBlink: A Wearable Device to Continuously Detect, Track, and Actuate Blinking For Alleviating Dry Eyes and Computer Vision Syndrome. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 1, 1, Article 1 (mar 2017), 19 pages. https://doi.org/10.1145/3053330
[10]
Michelle Elliott, Heidi Fandrich, Trefford Simpson, and Desmond Fonn. 1998. Analysis of the repeatability of tear break-up time measurement techniques on asymptomatic subjects before, during and after contact lens wear. Contact Lens and Anterior Eye 21, 4 (1998), 98--103. https://doi.org/10.1016/S1367-0484(98)80002-7
[11]
Kimberly F Farrand, Moshe Fridman, Ipek özer Stillman, and Debra A Schaumberg. 2017. Prevalence of diagnosed dry eye disease in the United States among adults aged 18 years and older. Am. J. Ophthalmol. 182 (Oct. 2017), 90--98.
[12]
A. Fogelton and W. Benesova. 2016. Eye blink detection based on motion vectors analysis. Computer Vision and Image Understanding 148 (2016), 23--33. https://doi.org/10.1016/j.cviu.2016.03.011 Special issue on Assistive Computer Vision and Robotics - "Assistive Solutions for Mobility, Communication and HMI".
[13]
Gary N. Foulks. 2003. Challenges and Pitfalls in Clinical Trials of Treatments for Dry Eye. The Ocular Surface 1, 1 (2003), 20--30. https://doi.org/10.1016/S1542-0124(12)70004-6
[14]
Frederick T Fraunfelder, James J Sciubba, and William D Mathers. 2012. The role of medications in causing dry eye. Journal of ophthalmology 2012 (2012).
[15]
G Fuentes-Páez, J M Herreras, Y Cordero, A Almaraz, M J González, and M Calonge. 2011. Lack of concordance between dry eye syndrome questionnaires and diagnostic tests. Arch. Soc. Esp. Oftalmol. 86, 1 (Jan. 2011), 3--7.
[16]
Siddhartha Gairola, Murtuza Bohra, Nadeem Shaheer, Navya Jayaprakash, Pallavi Joshi, Anand Balasubramaniam, Kaushik Murali, Nipun Kwatra, and Mohit Jain. 2022. SmartKC: Smartphone-Based Corneal Topographer for Keratoconus Detection. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 5, 4, Article 155 (dec 2022), 27 pages. https://doi.org/10.1145/3494982
[17]
Daniele Gaudenzi, Tommaso Mori, Salvatore Crugliano, Antonella Grasso, Carlo Frontini, Antonella Carducci, Siddharth Yadav, Roberto Sgrulletta, Emiliano Schena, Marco Coassin, and Antonio Di Zazzo. 2022. AS-OCT and Ocular Hygrometer as Innovative Tools in Dry Eye Disease Diagnosis. Applied Sciences 12, 3 (2022). https://doi.org/10.3390/app12031647
[18]
Johnny Gayton. 2009. Etiology, prevalence, and treatment of dry eye disease. Clinical ophthalmology (Auckland, N.Z.) 3 (02 2009), 405--12. https://doi.org/10.2147/OPTH.S5555
[19]
Tomoko Goto, Xiaodong Zheng, Stephen D Klyce, Hisashi Kataoka, Toshihiko Uno, Mike Karon, Yoshiyuki Tatematsu, Takeo Bessyo, Kazuo Tsubota, and Yuichi Ohashi. 2003. A new method for tear film stability analysis using videokeratography. American Journal of Ophthalmology 135, 5 (2003), 607--612. https://doi.org/10.1016/S0002-9394(02)02221-3
[20]
Koray Gumus, Charlene Hong Crockett, Kavita Rao, Elizabeth Yeu, Mitchell P. Weikert, Mariko Shirayama, Shigeki Hada, and Stephen C. Pflugfelder. 2011. Noninvasive Assessment of Tear Stability with the Tear Stability Analysis System in Tear Dysfunction Patients. Investigative Ophthalmology & Visual Science 52, 1 (01 2011), 456--461. https://doi.org/10.1167/iovs.10-5292 arXiv:https://arvojournals.org/arvo/content_public/journal/iovs/932967/z7g00111000456.pdf
[21]
Yuting Hong and Makoto Hasegawa. 2021. Proposal of Tear Meniscus Measurement for Minor Dry-eye Detection Using Smart-phone Camera and Ring-light. In 2021 36th International Technical Conference on Circuits/Systems, Computers and Communications (ITC-CSCC). 1--4. https://doi.org/10.1109/ITC-CSCC52171.2021.9501487
[22]
Takenori Inomata, Masao Iwagami, Masahiro Nakamura, Tina Shiang, Keiichi Fujimoto, Yuichi Okumura, Nanami Iwata, Kenta Fujio, Yoshimune Hiratsuka, Satoshi Hori, Kazuo Tsubota, Reza Dana, and Akira Murakami. 2020. Association between dry eye and depressive symptoms: Large-scale crowdsourced research using the DryEyeRhythm iPhone application. The Ocular Surface 18, 2 (2020), 312--319. https://doi.org/10.1016/j.jtos.2020.02.007
[23]
Takenori Inomata, Masahiro Nakamura, Masao Iwagami, Akie Midorikawa-Inomata, Jaemyoung Sung, Keiichi Fujimoto, Yuichi Okumura, Atsuko Eguchi, Nanami Iwata, Maria Miura, Kenta Fujio, Ken Nagino, Satoshi Hori, Kazuo Tsubota, Reza Dana, and Akira Murakami. 2020. Stratification of Individual Symptoms of Contact Lens-Associated Dry Eye Using the iPhone App DryEyeRhythm: Crowdsourced Cross-Sectional Study. J Med Internet Res 22, 6 (26 Jun 2020), e18996. https://doi.org/10.2196/18996
[24]
Takenori Inomata, Masahiro Nakamura, Masao Iwagami, Tina Shiang, Yusuke Yoshimura, Keiichi Fujimoto, Yuichi Okumura, Atsuko Eguchi, Nanami Iwata, Maria Miura, Satoshi Hori, Yoshimune Hiratsuka, Miki Uchino, Kazuo Tsubota, Reza Dana, and Akira Murakami. 2019. Risk Factors for Severe Dry Eye Disease: Crowdsourced Research Using DryEyeRhythm. Ophthalmology 126, 5 (2019), 766--768. https://doi.org/10.1016/j.ophtha.2018.12.013
[25]
Takenori Inomata, Masahiro Nakamura, Jaemyoung Sung, Akie Midorikawa-Inomata, Masao Iwagami, Kenta Fujio, Yasutsugu Akasaki, Yuichi Okumura, Keiichi Fujimoto, Atsuko Eguchi, Maria Miura, Ken Nagino, Hurramhon Shokirova, Jun Zhu, Mizu Kuwahara, Kunihiko Hirosawa, Reza Dana, and Akira Murakami. 2021. Smartphone-based digital phenotyping for dry eye toward P4 medicine: a crowdsourced cross-sectional study. npj Digital Medicine 4, 1 (20 Dec 2021), 171. https://doi.org/10.1038/s41746-021-00540-2
[26]
LV Prasad Eye Institute. 2019. Dry Eye Disease Big Data Study. Retrieved Apr 1, 2020 from https://www.lvpei.org/media-event/dry-eye-disease-big-data-study
[27]
Abraham Kayal. 2021. The Physiology of Tear Film. In Dry Eye Syndrome, Felicia M. Ferreri (Ed.). IntechOpen, Rijeka, Chapter 2. https://doi.org/10.5772/intechopen.98945
[28]
Robert H Kennedy, William M Bourne, and John A Dyer. 1986. A 48-year clinical and epidemiologic study of keratoconus. American journal of ophthalmology 101, 3 (1986), 267--273.
[29]
P. Ewen King-Smith, Barbara A. Fink, Jason J. Nichols, Kelly K. Nichols, Richard J. Braun, and Geoffrey B. McFadden. 2009. The Contribution of Lipid Layer Movement to Tear Film Thinning and Breakup. Investigative Ophthalmology & Visual Science 50, 6 (06 2009), 2747--2756. https://doi.org/10.1167/iovs.08-2459
[30]
P Ewen King-Smith, Erich A Hinel, and Jason J Nichols. 2009. Application of a novel interferometric method to investigate the relation between lipid layer thickness and tear film thinning. Invest Ophthalmol Vis Sci 51, 5 (Dec. 2009), 2418--2423.
[31]
P Ewen King-Smith, Samuel H Kimball, and Jason J Nichols. 2014. Tear film interferometry and corneal surface roughness. Invest Ophthalmol Vis Sci 55, 4 (April 2014), 2614--2618.
[32]
Stephen R. Tonge Lakhbir S. Mengher, Anthony J. Bron and David J. Gilbert. 1985. A non-invasive instrument for clinical assessment of the pre-corneal tear film stability. Current Eye Research 4, 1 (1985), 1--7. https://doi.org/10.3109/02713688508999960 arXiv:https://doi.org/10.3109/02713688508999960 3979089.
[33]
Eric C. Larson, Mayank Goel, Gaetano Boriello, Sonya Heltshe, Margaret Rosenfeld, and Shwetak N. Patel. 2012. SpiroSmart: using a microphone to measure lung function on a mobile phone. In Proceedings of the 2012 ACM Conference on Ubiquitous Computing (Pittsburgh, Pennsylvania) (UbiComp '12). Association for Computing Machinery, New York, NY, USA, 280--289. https://doi.org/10.1145/2370216.2370261
[34]
Euihyeok Lee, Chulhong Min, and Seungwoo Kang. 2018. Towards a Wearable Assistant to Prevent Computer Vision Syndrome. In Proceedings of the 2018 ACM International Joint Conference and 2018 International Symposium on Pervasive and Ubiquitous Computing and Wearable Computers (Singapore, Singapore) (UbiComp '18). Association for Computing Machinery, New York, NY, USA, 122--125. https://doi.org/10.1145/3267305.3267587
[35]
Ryan Lee, Sharon Yeo, Han Tun Aung, and Louis Tong. 2016. Agreement of noninvasive tear break-up time measurement between Tomey RT-7000 Auto Refractor-Keratometer and Oculus Keratograph 5M. Clin. Ophthalmol. 10 (Sept. 2016), 1785--1790.
[36]
Tian Lei, Song Wenxiu, Wang Zhiqun, Zhang Yang, and Sun Xuguang. 2017. Diagnosis of dry eye disease using keratograph 5M. Journal of Capital Medical University 38, 1, Article 11 (2017), 5 pages. https://doi.org/10.3969/j.issn.1006-7795.2017.01.003
[37]
Hui Lu, Michael R Wang, Jianhua Wang, and Meixiao Shen. 2014. Tear film measurement by optical reflectometry technique. J Biomed Opt 19, 2 (Feb. 2014), 027001.
[38]
Alex Mariakakis, Jacob Baudin, Eric Whitmire, Vardhman Mehta, Megan A. Banks, Anthony Law, Lynn Mcgrath, and Shwetak N. Patel. 2017. PupilScreen: Using Smartphones to Assess Traumatic Brain Injury. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 1, 3, Article 81 (sep 2017), 27 pages. https://doi.org/10.1145/3131896
[39]
Paul McCann, Alison G Abraham, Adhuna Mukhopadhyay, Kanella Panagiotopoulou, Hongan Chen, Thanitsara Rittiphairoj, Darren G Gregory, Scott G Hauswirth, Cristos Ifantides, Riaz Qureshi, Su-Hsun Liu, Ian J Saldanha, and Tianjing Li. 2022. Prevalence and incidence of dry eye and meibomian gland dysfunction in the United States: A systematic review and meta-analysis. JAMA Ophthalmol. 140, 12 (Dec. 2022), 1181--1192.
[40]
Marguerite McDonald, Dipen A Patel, Michael S Keith, and Sonya J Snedecor. 2016. Economic and humanistic burden of dry eye disease in Europe, North America, and Asia: A systematic literature review. Ocul. Surf. 14, 2 (April 2016), 144--167.
[41]
Kenneth J Blades Michael Tm Wang, Paul J Murphy and Jennifer P Craig. 2018. Comparison of non-invasive tear film stability measurement techniques. Clinical and Experimental Optometry 101, 1 (2018), 13--17. https://doi.org/10.1111/cxo.12546 arXiv:https://doi.org/10.1111/cxo.12546 28503827.
[42]
Akie Midorikawa-Inomata, Takenori Inomata, Shuko Nojiri, Masahiro Nakamura, Masao Iwagami, Keiichi Fujimoto, Yuichi Okumura, Nanami Iwata, Atsuko Eguchi, Hitomi Hasegawa, Hikaru Kinouchi, Akira Murakami, and Hiroyuki Kobayashi. 2019. Reliability and validity of the Japanese version of the Ocular Surface Disease Index for dry eye disease. BMJ Open 9, 11 (2019). https://doi.org/10.1136/bmjopen-2019-033940 arXiv:https://bmjopen.bmj.com/content/9/11/e033940.full.pdf
[43]
Jun Moon, Kyoung Woo Kim, and Nam Moon. 2016. Smartphone use is a risk factor for pediatric dry eye disease according to region and age: a case control study. BMC Ophthalmology 16 (12 2016). https://doi.org/10.1186/s12886-016-0364-4
[44]
J E Moore, J E Graham, E A Goodall, D A Dartt, A Leccisotti, V E McGilligan, and T C B Moore. 2009. Concordance between common dry eye diagnostic tests. Br. J. Ophthalmol. 93, 1 (Jan. 2009), 66--72.
[45]
Ken Nagino, Yuichi Okumura, Masahiro Yamaguchi, Jaemyoung Sung, Masashi Nagao, Kenta Fujio, Yasutsugu Akasaki, Tianxiang Huang, Kunihiko Hirosawa, Masao Iwagami, Akie Midorikawa-Inomata, Keiichi Fujimoto, Atsuko Eguchi, Yukinobu Okajima, Koji Kakisu, Yuto Tei, Takefumi Yamaguchi, Daisuke Tomida, Masaki Fukui, Yukari Yagi-Yaguchi, Yuichi Hori, Jun Shimazaki, Shuko Nojiri, Yuki Morooka, Alan Yee, Maria Miura, Mizu Ohno, and Takenori Inomata. 2023. Diagnostic Ability of a Smartphone App for Dry Eye Disease: Protocol for a Multicenter, Open-Label, Prospective, and Cross-sectional Study. JMIR Res Protoc 12 (13 Mar 2023), e45218. https://doi.org/10.2196/45218
[46]
Yuichi Okumura, Takenori Inomata, Akie Midorikawa-Inomata, Jaemyoung Sung, Kenta Fujio, Yasutsugu Akasaki, Masahiro Nakamura, Masao Iwagami, Keiichi Fujimoto, Atsuko Eguchi, Maria Miura, Ken Nagino, Kunihiko Hirosawa, Tianxiang Huang, Mizu Kuwahara, Reza Dana, and Akira Murakami. 2022. DryEyeRhythm: A reliable and valid smartphone application for the diagnosis assistance of dry eye. The Ocular Surface 25 (2022), 19--25. https://doi.org/10.1016/j.jtos.2022.04.005
[47]
Sudi Patel and Larysa Tutchenko. 2019. The refractive index of the human cornea: A review. Cont Lens Anterior Eye 42, 5 (May 2019), 575--580.
[48]
Stephen Pflugfelder, Lauren Nakhleh, Yasushi Kikukawa, Shin Tanaka, and Takuya Kosugi. 2022. Non-invasive tear break-up detection with the Kowa DR-1α and its relationship to dry eye clinical severity. Int. J. Mol. Sci. 23, 23 (Nov. 2022), 14774.
[49]
Ruth Miyuki Santo, Felipe Ribeiro-Ferreira, Milton Ruiz Alves, Jonathan Epstein, and Priscila Novaes. 2015. Enhancing the cross-cultural adaptation and validation process: linguistic and psychometric testing of the Brazilian-Portuguese version of a self-report measure for dry eye. Journal of Clinical Epidemiology 68, 4 (2015), 370--378. https://doi.org/10.1016/j.jclinepi.2014.07.009
[50]
Rhett M. Schiffman, Murray Dale Christianson, Gordon Jacobsen, Jan D. Hirsch, and Brenda L. Reis. 2000. Reliability and Validity of the Ocular Surface Disease Index. Archives of Ophthalmology 118, 5 (05 2000), 615--621. https://doi.org/10.1001/archopht.118.5.615 arXiv:https://jamanetwork.com/journals/jamaophthalmology/articlepdf/413145/ecs90139.pdf
[51]
Chika Shigeyasu, Masakazu Yamada, Norihiko Yokoi, Motoko Kawashima, Kazuhisa Suwaki, Miki Uchino, Yoshimune Hiratsuka, Kazuo Tsubota, and On Behalf Of The Decs-J Study Group. 2020. Characteristics and utility of fluorescein breakup patterns among dry eyes in clinic-based settings. Diagnostics (Basel) 10, 9 (Sept. 2020).
[52]
Swati Singh, Saumya Srivastav, Zarin Modiwala, Mohammed Hasnat Ali, and Sayan Basu. 2023. Repeatability, reproducibility and agreement between three different diagnostic imaging platforms for tear film evaluation of normal and dry eye disease. Eye 37, 10 (01 Jul 2023), 2042--2047. https://doi.org/10.1038/s41433-022-02281-2
[53]
John E. Sutphin, Gui-shuang Ying, Vatinee Y. Bunya, Yinxi Yu, Meng C. Lin, Kathleen McWilliams, Elizabeth Schmucker, Eric J. Kuklinski, Penny A. Asbell, Maureen G. Maguire, for the Dry Eye Assessment, and Management (DREAM) Study Research Group. 2022. Correlation of Measures From the OCULUS Keratograph and Clinical Assessments of Dry Eye Disease in the Dry Eye Assessment and Management Study. Cornea 41, 7 (2022). https://journals.lww.com/corneajrnl/fulltext/2022/07000/correlation_of_measures_from_the_oculus.7.aspx
[54]
Deborah F. Sweeney, Thomas J. Millar, and Shiwani R. Raju. 2013. Tear film stability: A review. Experimental Eye Research 117 (2013), 28--38. https://doi.org/10.1016/j.exer.2013.08.010 Tears: A Unique Mucosal Surface Secretion.
[55]
Maho Taniai, Kaito Okazaki, and Makoto Hasegawa. 2023. Improvement of Tear Meniscus Measurement for Dry Eye Detection Using Smartphone and Ring Light. In 2023 IEEE International Conference on Consumer Electronics-Asia (ICCE-Asia). 1--4. https://doi.org/10.1109/ICCE-Asia59966.2023.10326431
[56]
Sania Vidas Pauk, Igor Petriček, Tomislav Jukić, Smiljka Popović-Suić, Martina Tomić, Miro Kalauz, Sonja Jandrokovic, and Sanja Masnec. 2019. Noninvasive tear film break-up time assessment using handheld lipid layer examination instrument. Acta Clin. Croat. 58, 1 (March 2019), 63--71.
[57]
Sania Vidas Pauk, Igor Petriček, Tomislav Jukić, Smiljka Popović-Suić, Martina Tomić, Miro Kalauz, Sonja Jandrokovic, and Sanja Masnec. 2019. Noninvasive tear film break-up time assessment using handheld lipid layer examination instrument. Acta Clin. Croat. 58, 1 (March 2019), 63--71.
[58]
Sania Vidas Pauk, Igor Petriček, Martina Tomić, Tomislav Bulum, Sonja Jandroković, Maja Pauk Gulić, Miro Kalauz, and Dina Lešin Gaćina. 2023. Diagnostic accuracy of non-invasive tear film break-up time assessed by the simple manual interferometric device. Contact Lens and Anterior Eye 46, 2 (2023), 101776. https://doi.org/10.1016/j.clae.2022.101776
[59]
Luca Vigo, Marco Pellegrini, Federico Bernabei, Francesco Carones, Vincenzo Scorcia, and Giuseppe Giannaccare. 2020. Diagnostic performance of a novel noninvasive workup in the setting of dry eye disease. J. Ophthalmol. 2020 (Dec. 2020), 5804123.
[60]
Edward Jay Wang, William Li, Doug Hawkins, Terry Gernsheimer, Colette Norby-Slycord, and Shwetak N. Patel. 2016. HemaApp: noninvasive blood screening of hemoglobin using smartphone cameras. In Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing (Heidelberg, Germany) (UbiComp '16). Association for Computing Machinery, New York, NY, USA, 593--604. https://doi.org/10.1145/2971648.2971653
[61]
Edward Jay Wang, Junyi Zhu, Mohit Jain, Tien-Jui Lee, Elliot Saba, Lama Nachman, and Shwetak N. Patel. 2018. Seismo: Blood Pressure Monitoring using Built-in Smartphone Accelerometer and Camera. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (Montreal QC, Canada) (CHI '18). Association for Computing Machinery, New York, NY, USA, 1--9. https://doi.org/10.1145/3173574.3173999
[62]
Mark D.P. Willcox, Pablo Argüeso, Georgi A. Georgiev, Juha M. Holopainen, Gordon W. Laurie, Tom J. Millar, Eric B. Papas, Jannick P. Rolland, Tannin A. Schmidt, Ulrike Stahl, Tatiana Suarez, Lakshman N. Subbaraman, Omür ö. Uçakhan, and Lyndon Jones. 2017. TFOS DEWS II Tear Film Report. The Ocular Surface 15, 3 (2017), 366--403. https://doi.org/10.1016/j.jtos.2017.03.006 TFOS International Dry Eye WorkShop (DEWS II).
[63]
James S Wolffsohn, Reiko Arita, Robin Chalmers, Ali Djalilian, Murat Dogru, Kathy Dumbleton, Preeya K Gupta, Paul Karpecki, Sihem Lazreg, Heiko Pult, Benjamin D Sullivan, Alan Tomlinson, Louis Tong, Edoardo Villani, Kyung Chul Yoon, Lyndon Jones, and Jennifer P Craig. 2017. TFOS DEWS II Diagnostic Methodology report. Ocul. Surf. 15, 3 (July 2017), 539--574.
[64]
Meng Xue, Yuyang Zeng, Shengkang Gu, Qian Zhang, Bowei Tian, and Changzheng Chen. 2024. SDE: Early Screening for Dry Eye Disease with Wireless Signals. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 7, 4, Article 194 (jan 2024), 23 pages. https://doi.org/10.1145/3631438
[65]
Sharon Yeo and Louis Tong. 2018. Coping with dry eyes: a qualitative approach. BMC ophthalmology 18 (2018), 1--9.
[66]
Junhua Yu, Carl V Asche, and Carol J Fairchild. 2011. The economic burden of dry eye disease in the United States: a decision tree analysis. Cornea 30, 4 (April 2011), 379--387.
[67]
Fabrizio Zeri, Giulia Carlotta Rizzo, Erika Ponzini, and Silvia Tavazzi. 2024. Comparing automated and manual assessments of tear break-up time using different non-invasive devices and a fluorescein procedure. Scientific Reports 14, 1 (30 Jan 2024), 2516. https://doi.org/10.1038/s41598-024-52686-0
[68]
Sydney Zhang and Julio Echegoyen. 2023. Design and Usability Study of a Point of Care mHealth App for Early Dry Eye Screening and Detection. Journal of Clinical Medicine 12, 20 (2023). https://doi.org/10.3390/jcm12206479
Index Terms
- DEDector: Smartphone-Based Noninvasive Screening of Dry Eye Disease
Recommendations
Enteroscopic findings of Celiac Disease and their correlation with mucosal histopathologic changes
Background and aimsSingle Balloon Enteroscopy enables us to examine the small bowel for various diseases. It provides a view of the intestinal mucosa with biopsy capability, which may be helpful in search of a mucosal disease such as Celiac Disease. ...
Impedance Cardiography Used For Diagnosis of Disease
WCI '15: Proceedings of the Third International Symposium on Women in Computing and InformaticsIn emergency medicine, hemodynamic parameters of a patient in extremely ill condition are difficult to evaluate. It is very difficult to confirm correct state of their cardiovascular health only from parameters measured by checking blood pressure & ...
Application of artificial intelligence techniques for non-alcoholic fatty liver disease diagnosis: A systematic review (2005–2023)
Highlights- NAFLD is a liver disease that is becoming more common throughout the world.
- This article provides a comprehensive review of the studies conducted in the area of utilizing artificial intelligence to determine the prevalence of NAFLD/...
Abstract Background and objectivesNon-alcoholic fatty liver disease (NAFLD) is a common liver disease with a rapidly growing incidence worldwide. For prognostication and therapeutic decisions, it is important to distinguish the pathological stages of ...
Comments
Information & Contributors
Information
Published In
Copyright © 2024 Owner/Author.
This work is licensed under a Creative Commons Attribution International 4.0 License.
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 21 November 2024
Published in IMWUT Volume 8, Issue 4
Check for updates
Author Tags
Qualifiers
- Research-article
- Research
- Refereed
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 220Total Downloads
- Downloads (Last 12 months)220
- Downloads (Last 6 weeks)82
Reflects downloads up to 02 Feb 2025
Other Metrics
Citations
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in