• Title/Summary/Keyword: blindness

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Long-term follow-up of optic neuritis associated with meningoencephalitis of unknown etiology in a Maltese dog

  • Jung, Sun-Jun;Kim, Jury;Plummer, Caryn E;Lee, Ki-Chang;Kim, Min-Su
    • Korean Journal of Veterinary Research
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    • v.59 no.2
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    • pp.113-117
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    • 2019
  • A 6-year-old intact male Maltese dog presented with a history of blindness and ataxia. Neuro-ophthalmic examination revealed dilated pupils with absent pupillary light reflexes and menace response in both eyes. Mild peripapillary edema was noted in the fundus of the right eye. After magnetic resonance imaging, the dog was provisionally diagnosed with meningoencephalitis of unknown etiology. Follow-up funduscopy was performed to monitor the condition of the optic discs for three years. Despite of the treatment with prednisolone, the optic nerve progressed to atrophy and the dog couldn't restore vision.

Thermal Display-Based Emotional Communication System for Blindness (시각장애인을 위한 온각 기반 감정 전달 시스템)

  • Noh, Hyoju;Kim, Kangtae;Lee, Sungkil
    • Annual Conference of KIPS
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    • 2013.11a
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    • pp.1659-1660
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    • 2013
  • 사람 간 의사소통에서 표정, 몸짓과 같은 비언어적 시각 요소들은 감정 표현의 중요한 요소이나, 시각장애인들은 이러한 감정 정보들을 받아들이는데 제한적이다. 본 논문은 시각장애인에게 이러한 비언어적 시각 요소 기반의 감정 정보를 인식하여 온각으로 전달하기 위한 방법론을 제안한다. 상대방의 표정은 안경 착용형 카메라로 인식되어 감정으로 분류된다. 인식된 표정이 웃는 얼굴과 같이 호감인 경우, 이 상태는 온각으로 변환되어 안경에 착용된 온도전달 장치에서 시각장애인에게 호감을 전달한다. 이러한 온각기반 감정전달 장치는 시각장애인의 의사소통 향상을 위한 장치의 개발에 응용될 수 있다.

A case report of cocklebur poisoning in Hanwoo (Korean native cattle) (한우에서 발생한 도꼬마리 중독 증례)

  • Jun, Kyoungah;Lee, DongEun;Jeong, DaeEun
    • Korean Journal of Veterinary Service
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    • v.44 no.2
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    • pp.113-117
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    • 2021
  • Cocklebur poisoning in livestock can cause sudden death, with clinical signs include depression, inappetite, blindness, reluctance to move, hypersensitivity, ataxia and coma. The cause of cocklebur poisoning is ingestion of cocklebur sprout or seed, which contains carboxyatractyloside. In December 2020, a 47 month-old Hanwoo suddenly developed ataxia, and died after several hours. Hay mixed cocklebur seeds was fed to Hanwoo for 4 days before the symptoms. At autopsy, petechia and ecchymosis were seen on serous membrane of rumen and intestines. Peritoneal cavities contained a yellowish fluid and, hypoglycemia (Glu <20 mg/dL) was measured in blood test result. Microscopic lesions were karyolysis of centriloular hepatocyte and hemorrhage. Based on autopsy, blood and histopathological test, we diagnosed this case as cocklebur poisoning in Hanwoo.

Feature Extraction of Non-proliferative Diabetic Retinopathy Using Faster R-CNN and Automatic Severity Classification System Using Random Forest Method

  • Jung, Younghoon;Kim, Daewon
    • Journal of Information Processing Systems
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    • v.18 no.5
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    • pp.599-613
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    • 2022
  • Non-proliferative diabetic retinopathy is a representative complication of diabetic patients and is known to be a major cause of impaired vision and blindness. There has been ongoing research on automatic detection of diabetic retinopathy, however, there is also a growing need for research on an automatic severity classification system. This study proposes an automatic detection system for pathological symptoms of diabetic retinopathy such as microaneurysms, retinal hemorrhage, and hard exudate by applying the Faster R-CNN technique. An automatic severity classification system was devised by training and testing a Random Forest classifier based on the data obtained through preprocessing of detected features. An experiment of classifying 228 test fundus images with the proposed classification system showed 97.8% accuracy.

The Investigation of Employing Supervised Machine Learning Models to Predict Type 2 Diabetes Among Adults

  • Alhmiedat, Tareq;Alotaibi, Mohammed
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.9
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    • pp.2904-2926
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    • 2022
  • Currently, diabetes is the most common chronic disease in the world, affecting 23.7% of the population in the Kingdom of Saudi Arabia. Diabetes may be the cause of lower-limb amputations, kidney failure and blindness among adults. Therefore, diagnosing the disease in its early stages is essential in order to save human lives. With the revolution in technology, Artificial Intelligence (AI) could play a central role in the early prediction of diabetes by employing Machine Learning (ML) technology. In this paper, we developed a diagnosis system using machine learning models for the detection of type 2 diabetes among adults, through the adoption of two different diabetes datasets: one for training and the other for the testing, to analyze and enhance the prediction accuracy. This work offers an enhanced classification accuracy as a result of employing several pre-processing methods before applying the ML models. According to the obtained results, the implemented Random Forest (RF) classifier offers the best classification accuracy with a classification score of 98.95%.

Retinopathy of prematurity: a review of epidemiology and current treatment strategies

  • Hong, Eun Hee;Shin, Yong Un;Cho, Heeyoon
    • Clinical and Experimental Pediatrics
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    • v.65 no.3
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    • pp.115-126
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    • 2022
  • Retinopathy of prematurity (ROP) is among the most common causes of childhood blindness. Three phases of ROP epidemics have been observed worldwide since ROP was first described in the 1940s. Despite advances in neonatal care, the occurrence of ROP and associated visual impairment has been increasing somewhere on Earth and remains difficult to control. Conventional treatment options for preventing ROP progression include retinal ablation using cryotherapy or laser therapy. With the emergence of anti-vascular endothelial growth factor (anti-VEGF) treatment for ocular diseases, the efficacy and safety of anti-VEGF therapy for ROP have recently been actively discussed. In the advanced stage of ROP with retinal detachment, surgical treatment including scleral buckling or vitrectomy is needed to maintain or induce retinal attachment. At this stage, the visual outcome is usually poor despite successful anatomical retinal attachment. Therefore, preventing ROP progression by timely screening examinations and treatment remains the most important part of ROP management.

Labor Vulnerability Assessment through Electroencephalogram Monitoring: a Bispectrum Time-frequency Analysis Approach

  • CHEN, Jiayu;Lin, Zhenghang
    • International conference on construction engineering and project management
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    • 2015.10a
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    • pp.179-182
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    • 2015
  • Detecting and assessing human-related risks is critical to improve the on-site safety condition and reduce the loss in lives, time and budget for construction industry. Recent research in neural science and psychology suggest inattentional blindness that caused by overload in working memory is the major cause of unexpected human related accidents. Due to the limitation of human mental workload, laborers are vulnerable to unexpected hazards while focusing on complicated and dangerous construction tasks. Therefore, detecting the risk perception abilities of workers could help to identify vulnerable individuals and reduce unexpected injuries. However, there are no available measurement approaches or devices capable of monitoring construction workers' mental conditions. The research proposed in this paper aims to develop such a measurement framework to evaluate hazards through monitoring electroencephalogram of labors. The research team developed a wearable safety monitoring helmet, which can collect the brain waves of users for analysis. A bispectrum approach has been developed in this paper to enrich the data source and improve accuracy.

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Machine Learning Techniques for Diabetic Retinopathy Detection: A Review

  • Rachna Kumari;Sanjeev Kumar;Sunila Godara
    • International Journal of Computer Science & Network Security
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    • v.24 no.4
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    • pp.67-76
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    • 2024
  • Diabetic retinopathy is a threatening complication of diabetes, caused by damaged blood vessels of light sensitive areas of retina. DR leads to total or partial blindness if left untreated. DR does not give any symptoms at early stages so earlier detection of DR is a big challenge for proper treatment of diseases. With advancement of technology various computer-aided diagnostic programs using image processing and machine learning approaches are designed for early detection of DR so that proper treatment can be provided to the patients for preventing its harmful effects. Now a day machine learning techniques are widely applied for image processing. These techniques also provide amazing result in this field also. In this paper we discuss various machine learning and deep learning based techniques developed for automatic detection of Diabetic Retinopathy.

A Prediction Model for the Development of Cataract Using Random Forests (Random Forests 기법을 이용한 백내장 예측모형 - 일개 대학병원 건강검진 수검자료에서 -)

  • Han, Eun-Jeong;Song, Ki-Jun;Kim, Dong-Geon
    • The Korean Journal of Applied Statistics
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    • v.22 no.4
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    • pp.771-780
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    • 2009
  • Cataract is the main cause of blindness and visual impairment, especially, age-related cataract accounts for about half of the 32 million cases of blindness worldwide. As the life expectancy and the expansion of the elderly population are increasing, the cases of cataract increase as well, which causes a serious economic and social problem throughout the country. However, the incidence of cataract can be reduced dramatically through early diagnosis and prevention. In this study, we developed a prediction model of cataracts for early diagnosis using hospital data of 3,237 subjects who received the screening test first and then later visited medical center for cataract check-ups cataract between 1994 and 2005. To develop the prediction model, we used random forests and compared the predictive performance of this model with other common discriminant models such as logistic regression, discriminant model, decision tree, naive Bayes, and two popular ensemble model, bagging and arcing. The accuracy of random forests was 67.16%, sensitivity was 72.28%, and main factors included in this model were age, diabetes, WBC, platelet, triglyceride, BMI and so on. The results showed that it could predict about 70% of cataract existence by screening test without any information from direct eye examination by ophthalmologist. We expect that our model may contribute to diagnose cataract and help preventing cataract in early stages.

The Epidemiological Study on the Cataract of the Rural Aged Population Using a Simplified Screening System (간편한 선별검사법에 의한 농촌 노인인구의 백내장에 대한 역학조사)

  • Park, Eun Kyoo
    • Journal of Korean Ophthalmic Optics Society
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    • v.5 no.1
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    • pp.165-171
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    • 2000
  • The purpose of this study is to determine the prevalence of cataracts in a rural area of Kyung-Buk province. Cataract is the main cause of blindness and visual impairment in the world. Recently, the number of age-related cataract surgeries has increased remarkably. In spite of such an increase in the number of patients, there are still many cataract patients with highly deteriorated visual function who have had no occasion to receive an ocular examination. In order to screen such patients the author assessed 636 individual(1272 eyes) aged 50 years or more who had wanted to be examined generally in two area. Chilgok and Munkyung, Kyung-Buk province using a simplified cataract screening system recently proposed by Sasaki et al. Kanazawa Medical University in Japan. The results obtained are as follows. The number of visual impairment patients in this study group was 493(77.5%). They were screened by cataract screening system. Primary screening examination detected 448 subjects to be suspected of cataract while the subsequent secondary examination narrowed this number of subjects to 308(48.4%). Final number of subjects to be diagnosed of cataract was 421(66.2%). The rate of incidence, according to the age, was 27.5% in the 50 year-olds age group, 62.5% in the 60's age group, 86.1% in the 70's age group and 94.3% in the 80's age group and upwards. This results concluded that cataract is the main cause of blindness and visual impairment and is an important public eye health care problem of aged population in rural Korea. Methods of tackling the cataract problem(both backlog and incident), and other eye health needs are recommended. The need to extend eye health service to the rural areas is emphasized.

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