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Does obesity make it more difficult to find veins?
Apr 30 , 2025
1.Thickening of subcutaneous fat - Deeper vein location: The subcutaneous fat layer of obese people is thicker, which may cause the veins to be covered by fat, making them deeper and difficult to accurately locate through visual observation or touch (palpation). - Blurred touch: Adipose tissue weakens the elastic touch of veins finder, making it difficult for medical staff to determine the locatio...
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Holding hands and looking at the eyes to help with diagnosis | Suddenly
May 14 , 2025
Common causes: tractional retinal detachment (TRD) is mainly caused by the traction of the fibrous vascular membrane on the surface of the retina or within the vitreous. Adult TRD is most commonly seen in proliferative diabetic retinopathy (PDR), retinal vein occlusion (RVO), retinal vasculitis and proliferative vitreoretinopathy (PVR). In addition, trauma, sickle cell retinopathy and uveitis, etc...
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What is the new technology for finding veins?
May 14 , 2025
The new technology for finding veins usually refers to one of the biometric technologies, namely vein recognition technology. Vein recognition is a biometric technology that verifies an individual's identity by scanning and analyzing the vein images of a person's fingers or hands. It uses the biological characteristics of the human venous system for identity authentication. These biological charac...
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What are the relevant foreign research and technological advancements regarding Vein Finder?
May 23 , 2025
1.The application of Doppler ultrasound technology in venous localization A research team from the Georgia Institute of Technology in the United States has developed a low-cost handheld device that uses Doppler ultrasound technology to quickly locate veins. This device distinguishes arteries from veins by emitting ultrasonic beams and analyzing blood flow reflection signals, and guides punctures i...
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The Next Generation of OCT Technology Poised to Take Off and How AI is Reshaping the Future of OCT
May 29 , 2025
When OCT meets artificial intelligence, a diagnostic revolution quietly arrives: Automatic lesion identification: The algorithm based on convolutional neural network (CNN) can complete the pathological analysis of ophthalmic OCT images within 0.3 seconds, identifying dozens of lesions such as macular holes and retinal detachment, with an accuracy rate exceeding 95% Real-time surgical navigation: D...
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