Drawbacks of artificial intelligence and their potential solutions in the healthcare sector

B Khan, H Fatima, A Qureshi, S Kumar… - Biomedical Materials & …, 2023 - Springer
Artificial intelligence (AI) has the potential to make substantial progress toward the goal of
making healthcare more personalized, predictive, preventative, and interactive. We believe …

Digital technology, tele-medicine and artificial intelligence in ophthalmology: A global perspective

JPO Li, H Liu, DSJ Ting, S Jeon, RVP Chan… - Progress in retinal and …, 2021 - Elsevier
The simultaneous maturation of multiple digital and telecommunications technologies in
2020 has created an unprecedented opportunity for ophthalmology to adapt to new models …

[HTML][HTML] The potential for artificial intelligence in healthcare

T Davenport, R Kalakota - Future healthcare journal, 2019 - Elsevier
The complexity and rise of data in healthcare means that artificial intelligence (AI) will
increasingly be applied within the field. Several types of AI are already being employed by …

f-AnoGAN: Fast unsupervised anomaly detection with generative adversarial networks

T Schlegl, P Seeböck, SM Waldstein, G Langs… - Medical image …, 2019 - Elsevier
Obtaining expert labels in clinical imaging is difficult since exhaustive annotation is time-
consuming. Furthermore, not all possibly relevant markers may be known and sufficiently …

Clinically applicable deep learning for diagnosis and referral in retinal disease

J De Fauw, JR Ledsam, B Romera-Paredes… - Nature medicine, 2018 - nature.com
The volume and complexity of diagnostic imaging is increasing at a pace faster than the
availability of human expertise to interpret it. Artificial intelligence has shown great promise …

[HTML][HTML] Artificial intelligence in retina

U Schmidt-Erfurth, A Sadeghipour, BS Gerendas… - Progress in retinal and …, 2018 - Elsevier
Major advances in diagnostic technologies are offering unprecedented insight into the
condition of the retina and beyond ocular disease. Digital images providing millions of …

Deep learning in ophthalmology: the technical and clinical considerations

DSW Ting, L Peng, AV Varadarajan, PA Keane… - Progress in retinal and …, 2019 - Elsevier
The advent of computer graphic processing units, improvement in mathematical models and
availability of big data has allowed artificial intelligence (AI) using machine learning (ML) …

Artificial intelligence using deep learning to screen for referable and vision-threatening diabetic retinopathy in Africa: a clinical validation study

V Bellemo, ZW Lim, G Lim, QD Nguyen, Y **e… - The Lancet Digital …, 2019 - thelancet.com
Background Radical measures are required to identify and reduce blindness due to
diabetes to achieve the Sustainable Development Goals by 2030. Therefore, we evaluated …

Utilization of artificial intelligence in disease prevention: Diagnosis, treatment, and implications for the healthcare workforce

SUD Wani, NA Khan, G Thakur, SP Gautam, M Ali… - Healthcare, 2022 - mdpi.com
Artificial intelligence (AI) has been described as one of the extremely effective and promising
scientific tools available to mankind. AI and its associated innovations are becoming more …

[HTML][HTML] Real-world outcomes in patients with neovascular age-related macular degeneration treated with intravitreal vascular endothelial growth factor inhibitors

H Mehta, A Tufail, V Daien, AY Lee, V Nguyen… - Progress in retinal and …, 2018 - Elsevier
Clinical trials identified intravitreal vascular endothelial growth factor inhibitors (anti-VEGF
agents) have the potential to stabilise or even improve visual acuity outcomes in …