AIMC Topic: Blindness

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An advanced fire detection system for assisting visually challenged people using recurrent neural network and sea-horse optimizer algorithm.

Scientific reports
The developing elderly population undergoes a high level of eyesight and mental impairment, which frequently results in a defeat of independence. That kind of person should do vital daily tasks like heating and cooking, with methods and devices inten...

Preventive and therapeutic strategies via health care delivery system to minimize sight-threatening diabetic retinopathy: a narrative review.

Current diabetes reports
PURPOSE OF REVIEW: To highlight various preventive and therapeutic strategies via health care delivery system to minimize sight-threatening diabetic retinopathy.

VIIDA and InViDe: computational approaches for generating and evaluating inclusive image paragraphs for the visually impaired.

Disability and rehabilitation. Assistive technology
BACKGROUND: Existing image description methods when used as Assistive Technologies often fall short in meeting the needs of blind or low vision (BLV) individuals. They tend to either compress all visual elements into brief captions, create disjointed...

Cost-effectiveness and cost-utility of community-based blinding fundus diseases screening with artificial intelligence: A modelling study from Shanghai, China.

Computers in biology and medicine
BACKGROUND: With application of artificial intelligence (AI) in the disease screening, process reengineering occurred simultaneously. Whether process reengineering deserves special emphasis in AI implementation in the community-based blinding fundus ...

Evaluating the accuracy of the Ophthalmologist Robot for multiple blindness-causing eye diseases: a multicentre, prospective study protocol.

BMJ open
INTRODUCTION: Early eye screening and treatment can reduce the incidence of blindness by detecting and addressing eye diseases at an early stage. The Ophthalmologist Robot is an automated device that can simultaneously capture ocular surface and fund...

A deep learning system for predicting time to progression of diabetic retinopathy.

Nature medicine
Diabetic retinopathy (DR) is the leading cause of preventable blindness worldwide. The risk of DR progression is highly variable among different individuals, making it difficult to predict risk and personalize screening intervals. We developed and va...

Initiation of China Alliance of Research in High Myopia (CHARM): protocol for an AI-based multimodal high myopia research biobank.

BMJ open
INTRODUCTION: High myopia is a pressing public health concern due to its increasing prevalence, younger trend and the high risk of blindness, particularly in East Asian countries, including China. The China Alliance of Research in High Myopia (CHARM)...

Deep learning innovations in diagnosing diabetic retinopathy: The potential of transfer learning and the DiaCNN model.

Computers in biology and medicine
Diabetic retinopathy (DR) is a significant cause of vision impairment, emphasizing the critical need for early detection and timely intervention to avert visual deterioration. Diagnosing DR is inherently complex, as it necessitates the meticulous exa...

Predicting glaucoma progression using deep learning framework guided by generative algorithm.

Scientific reports
Glaucoma is a slowly progressing optic neuropathy that may eventually lead to blindness. To help patients receive customized treatment, predicting how quickly the disease will progress is important. Structural assessment using optical coherence tomog...

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...