AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Blindness

Showing 11 to 20 of 36 articles

Clear Filters

Minimized Computations of Deep Learning Technique for Early Diagnosis of Diabetic Retinopathy Using IoT-Based Medical Devices.

Computational intelligence and neuroscience
Diabetes mellitus is the main cause of diabetic retinopathy, the most common cause of blindness worldwide. In order to slow down or prevent vision loss and degeneration, early detection and treatment are essential. For the purpose of detecting and cl...

A Midbrain Inspired Recurrent Neural Network Model for Robust Change Detection.

The Journal of neuroscience : the official journal of the Society for Neuroscience
We present a biologically inspired recurrent neural network (RNN) that efficiently detects changes in natural images. The model features sparse, topographic connectivity (st-RNN), closely modeled on the circuit architecture of a "midbrain attention n...

UNav: An Infrastructure-Independent Vision-Based Navigation System for People with Blindness and Low Vision.

Sensors (Basel, Switzerland)
Vision-based localization approaches now underpin newly emerging navigation pipelines for myriad use cases, from robotics to assistive technologies. Compared to sensor-based solutions, vision-based localization does not require pre-installed sensor i...

Deciphering multiple sclerosis disability with deep learning attention maps on clinical MRI.

NeuroImage. Clinical
The application of convolutional neural networks (CNNs) to MRI data has emerged as a promising approach to achieving unprecedented levels of accuracy when predicting the course of neurological conditions, including multiple sclerosis, by means of ext...

Using Deep Learning Architectures for Detection and Classification of Diabetic Retinopathy.

Sensors (Basel, Switzerland)
Diabetic retinopathy (DR) is a common complication of long-term diabetes, affecting the human eye and potentially leading to permanent blindness. The early detection of DR is crucial for effective treatment, as symptoms often manifest in later stages...

Deep learning for automated detection of neovascular leakage on ultra-widefield fluorescein angiography in diabetic retinopathy.

Scientific reports
Diabetic retinopathy is a leading cause of blindness in working-age adults worldwide. Neovascular leakage on fluorescein angiography indicates progression to the proliferative stage of diabetic retinopathy, which is an important distinction that requ...

Review of Visualization Approaches in Deep Learning Models of Glaucoma.

Asia-Pacific journal of ophthalmology (Philadelphia, Pa.)
Glaucoma is a major cause of irreversible blindness worldwide. As glaucoma often presents without symptoms, early detection and intervention are important in delaying progression. Deep learning (DL) has emerged as a rapidly advancing tool to help ach...

Novel use of robot-assisted gait rehabilitation in a patient with stroke and blindness.

BMJ case reports
Robot-assisted gait training (RAGT) is an effective adjunctive treatment for patients with stroke that helps to regain functional mobility and is applied in many rehabilitation units for poststroke neurorecovery. We discuss our successful attempt to ...

Plant blindness and diversity in AI language models.

Trends in plant science
Large language models (LLMs) will benefit science by accelerating task performance. We explored whether answers generated by ChatGPT (generative pretrained transformer) to questions of biology are sufficiently diverse. 'Plant awareness' in ChatGPT an...