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Ischemic and haemorrhagic stroke risk estimation using a machine-learning-based retinal image analysis
ConclusionA fast and fully automatic method can be used for stroke subtype risk assessment and classification based on fundus photographs alone.
Source: Frontiers in Neurology - August 22, 2022 Category: Neurology Source Type: research

Light-Induced Pupillary Responses in Alzheimer's Disease
Light-Induced Pupillary Responses in Alzheimer's Disease Pratik S. Chougule1, Raymond P. Najjar1,2, Maxwell T. Finkelstein1, Nagaendran Kandiah3,4 and Dan Milea1,2,5* 1Department of Visual Neurosciences, Singapore Eye Research Institute, Singapore, Singapore 2The Ophthalmology & Visual Sciences ACP, Duke-National University of Singapore (NUS) Medical School, Singapore, Singapore 3Department of Neurology, National Neuroscience Institute, Singapore, Singapore 4Duke-National University of Singapore (NUS), Singapore, Singapore 5Singapore National Eye Centre, Singapore, Singapore The impact of Alzhe...
Source: Frontiers in Neurology - April 11, 2019 Category: Neurology Source Type: research

Multimodal Optical Diagnostics of the Microhaemodynamics in Upper and Lower Limbs
Conclusion The use of optical non-invasive diagnostic methods has a great potential for the detection of concomitant microcirculation disorders in patients with rheumatic diseases and diabetes. In this review, it was shown that the use of laser Doppler flowmetry, optical tissue oximetry and fluorescence spectroscopy together or separately may have important diagnostic value for the detection of violations, assessment of their severity, as well as for the analysis of the effectiveness of the therapy. The joint application of the considered technologies with the methods of machine learning (discriminant analysis) can be use...
Source: Frontiers in Physiology - April 15, 2019 Category: Physiology Source Type: research

Sensors, Vol. 22, Pages 4310: Cardiovascular Disease Diagnosis from DXA Scan and Retinal Images Using Deep Learning
In this study, we aimed at diagnosing CVD using a novel approach integrating information from retinal images and DXA data. We considered an adult Qatari cohort of 500 participants from Qatar Biobank (QBB) with an equal number of participants from the CVD and the control groups. We designed a case-control study with a novel multi-modal (combining data from multiple modalities—DXA and retinal images)—to propose a deep learning (DL)-based technique to distinguish the CVD group from the control group. Uni-modal models based on retinal images and DXA data achieved 75.6% and 77.4% accuracy, respective...
Source: Sensors - June 7, 2022 Category: Biotechnology Authors: Hamada R. H. Al-Absi Mohammad Tariqul Islam Mahmoud Ahmed Refaee Muhammad E. H. Chowdhury Tanvir Alam Tags: Article Source Type: research