Automated Early Prediction of Anomalies Due to Diabetes Using Fundus Images

2022 ◽  
pp. 176-200
Author(s):  
Sharmila Devi Sivakumar ◽  
Vaishnavi Seenuvasan ◽  
Gunasri B. ◽  
Balaji Srinivasan
Keyword(s):  
High Accuracy ◽  
Machine Learning Algorithms ◽  
Fundus Images ◽  
Healthy Life ◽  
Income Groups ◽  
Glaucoma Detection ◽  
Learning Techniques ◽  
The World ◽  
The Common ◽  
The Many

Diabetes is one of the common diseases in the world that cannot be permanently cured, but with proper medication one can lead a long and healthy life by curbing extreme complications. The skills and equipment required to identify the conditions take a longer time to provide an accurate result and are not an affordable means for all the income groups. In order to overcome this issue, an ML model is created and deployed in an application so it will be used by many in predicting the presence of the disease. The chapter focuses on detecting the presence of two major anomalies, namely diabetic retinopathy (DR) and glaucoma, which were caused due to diabetes. All the dataset used for the project is gathered from Kaggle and Messidor. Around six machine learning algorithms that fall under supervised learning techniques are executed. Among the many models, the random forest model has a high accuracy of 73% for DR prediction. Simultaneously, glaucoma detection is performed using different algorithms showing that Naive Bayes has the highest accuracy of 98%.

The Postcolonial Condition

2012 ◽  
Author(s):  
Robert J.C. Young
Keyword(s):  
Twentieth Century ◽  
Cultural Production ◽  
Postcolonial Theory ◽  
Colonial Rule ◽  
The World ◽  
The Common ◽  
The Many

The phrase ‘the postcolonial condition’ is usually invoked with respect to the particular state, as well as the common circumstances, of the many colonies that were freed from colonial rule during the second half of the twentieth century and are now living on the legacy of colonialism. Postcolonial conditions all over the world remain very substantially the product of European rule, given the extent of the European empires. While the rest of the world gradually frees itself from its postcoloniality, as it earlier freed itself from the shackles of colonialism, it is the Europe from which colonialism came that remains caught within the postcolonial condition: for this reason, the idea of ‘the postcolonial’ has had most currency in Europe. One aspect of the European postcolonial condition was the refusal to recognise its overall historical inevitability even as the decolonisation process was taking place. This article discusses the postcolonial condition in Europe, along with cultural production as well as postcolonial theory and Islam.

scholarly journals Effective Methodology for Co-Referential Aspect Based Sentiment Analysis of Tourist Reviews

2020 ◽  
pp. 523-529
Author(s):  
Kamlesh A. Waghmare ◽  
Sheetal K. Bhala
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Sentiment Analysis ◽  
High Accuracy ◽  
Machine Learning Algorithms ◽  
Data Sets ◽  
Knowledge Processing ◽  
The Neural Network ◽  
The World ◽  
Sentiment Score

Tourist reviews are the source of data that is going to be used for the travelers around the world to find the hotels for their stay according to their comfort. In this the hotels are ranked over the parameters or aspects considered keeping travelers in mind. This computation of data sets is done with the help of the machine learning algorithms and the neural network. The knowledge processing done over the reviews generates the sentiment score for each hotel with respect to the aspects defined. Here, the explicit , implicit and co-referential aspects are identified by suppressing the noise. This paper proposes the method that can be best used for the detection of the sentiments with the high accuracy.

scholarly journals EXPRESSED EMOTION IN THE CONTEXT OF THE ATTITUDE TOWARDS SELF, OTHERS AND THE WORLD

2021 ◽  
pp. 55-61
Author(s):  
Pastryk T.V.
Keyword(s):  
Quality Of Life ◽  
Expressed Emotion ◽  
Medical Condition ◽  
Research Subjects ◽  
Methodological Basis ◽  
Theoretical Approaches ◽  
The World ◽  
The Common ◽  
The Many

The article aims to explore the concepts of attitude and expressed emotion in the modern foreign and domestic Psychology.The study applies the method of theoretical comparative analysis. The common and different features of the concepts of attitude and expressed emotion were revealed according to the parameters, particularly content of the concepts, the first application, theoretical approaches and models, methods and measures of the research, subjects, objects and main features.The results of the study indicate that expressed emotion include warmth, hostility, criticism and emotional overwhelming, while attitude is represented by attitude towards self, others and the world. The results also show that attitude is deeply connected with personality’s values, while expressed emotion is mostly related to the attitude towards others. The study indicates that expressed emotion and attitude have a great impact on quality of life of the individuals with medical conditions. The results also indicate that the main features for attitude are modality (negative, positive, ambivalent), range and intensity, while the main features for expressed emotion are modality (positive, negative) and level (high, medium, low). The conclusion of the article underlines that the main problem aligned with expressed emotion study is the many of empirical results and the lack of methodological basis to generalize it. From this perspective the methodological basis for research of the category of attitude is the most appropriate. The prospects of the study are to develop the methodological basis for research of the category of attitude in the context of expressed emotion towards individuals with medical condition.Key words: expressed emotion, attitude, attitude towards self, others and the world, individuals with medical condition. Метою роботи є здійснення теоретичного зіставного аналізу конструкту емоційної експресивності та категорії ставлення в сучасній зарубіжній і вітчизняній літературі. Методом дослідження є теоретичне вивчення літератури в сукупності аналізу, синтезу та узагальнення.Результати дослідження свідчать про те, що категорія ставлення пов’язана із ціннісно-смисловою сферою особистості та визначається ставленням до себе, до інших і до світу. Виокремлено поняття експресивної емоційності як сукупності теплоти, критичності, емоційної гіперопіки та ворожості. Встановлено негативний вплив емоційної експресивності на якість життя особи з хронічними захворюваннями. З’ясовано, що наявні емпіричні дані, представлені в сучасних зарубіжних дослідженнях, важко концептуалізуються через брак єдиного методологічного підходу до дослідження емоційної експресивності, незважаючи на достатню кількість методик для її експериментального вивчення. У висновках дослідження представлено спільні й відмінні ознаки ставлення та емоційної експресивності за такими критеріями, як зміст понять, історія виникнення, теоретичні підходи й моделі, методи дослідження, суб’єкти, об’єкти, параметри. Визначено, що найважливішою відмінністю цих понять є ширший діапазон ставлення порівняно з емоційною експресивністю, а також зв’язок ставлення із ціннісно-смисловою сферою особистості. У цьому контексті вагомого значення набуває поняття самоставлення, яке слугує причиною високого рівня емоційної експресивності щодо інших. Попри можливе існування значної кількості об’єктів ставлення, у контексті нашого дослідження провідного значення набувають об’єкти здоров’я та хвороби, оскільки саме вони пов’язані з рівнем емоційної експресивності. Іншим важливим аспектом є види емоційної експресивності в межах категорії ставлення та їхні параметри. Найбільш поширеними для опису емоційної експресивності вважаються модуси та рівні, тоді як для визначення категорії ставлення оперують параметрами модусу, інтенсивності і широти. Перспективами дослідження є комплексне вивчення емоційної експресивності з виробленням методологічних засад дослідження та з огляду на вивчення категорії ставлення, а також підходи рис особистості, каузальної атрибуції і діатезного стресу.Ключові слова: емоційна експресивність, ставлення, ставлення до себе, ставлення до інших, ставлення до світу, особи з хронічними захворюваннями.

Education and the Study of Man

Antiquity ◽  
1943 ◽  
Vol 17 (67) ◽  
pp. 113-121 ◽  
Author(s):  
Grahame Clark
Keyword(s):  
Public Interest ◽  
New World ◽  
Full Measure ◽  
Military Power ◽  
The World ◽  
The Common ◽  
Common Man ◽  
Post War ◽  
The Many

Ducation as a subject for post-war planning is on everyone’s lips today. E Public interest has never been higher. Yet it may be doubted whether even now the full measure of its importance is realized. Next to winning the war, nothing is of greater moment than the battle for enlightenment, for if this is lost the ‘victory’ will be vain and we may all prepare for an ordeal more terrible than the present, because fought out among still larger aggregations of political and military power. The whole of history bears witness to the corruption of power, the struggles of the few for spoil of the many, the ignorance of the peoples and its lethal consequences to themselves. Today, thanks for the most part to the heroism of the common man, whether citizen of a bombed city, defender of Stalingrad, peasant of China, inhabitant of oppressed Europe or member of the forces of liberation, we stand on the threshold of what could be a new world: whether we cross that threshold or are elbowed back into the dark passage that leads to another holocaust, depends primarily on our attitude to education, on the steps taken during the next few years to bring to the common man everywhere a realization of his inheritance as a citizen of the world and an awareness of his power to mould his own destiny. What is needed above all is an overriding sense of human solidarity such as can come only from consciousness of common origins. Divided we fall victims to tribal leaders: united we may yet move forward to a life of elementary decency.

scholarly journals Improving Coronavirus (COVID-19) Diagnosis using Deep Transfer Learning

2020 ◽  
Author(s):  
Arshia Rehman ◽  
Saeeda Naz ◽  
Ahmed Khan ◽  
Ahmad Zaib ◽  
Imran Razzak
Keyword(s):  
Deep Learning ◽  
Transfer Learning ◽  
Bacterial Pneumonia ◽  
State Of The Art ◽  
High Accuracy ◽  
X Rays ◽  
Early Screening ◽  
X Ray ◽  
Learning Techniques ◽  
The World

AbstractBackgroundCoronavirus disease (COVID-19) is an infectious disease caused by a new virus. Exponential growth is not only threatening lives, but also impacting businesses and disrupting travel around the world.AimThe aim of this work is to develop an efficient diagnosis of COVID-19 disease by differentiating it from viral pneumonia, bacterial pneumonia and healthy cases using deep learning techniques.MethodIn this work, we have used pre-trained knowledge to improve the diagnostic performance using transfer learning techniques and compared the performance different CNN architectures.ResultsEvaluation results using K-fold (10) showed that we have achieved state of the art performance with overall accuracy of 98.75% on the perspective of CT and X-ray cases as a whole.ConclusionQuantitative evaluation showed high accuracy for automatic diagnosis of COVID-19. Pre-trained deep learning models develop in this study could be used early screening of coronavirus, however it calls for extensive need to CT or X-rays dataset to develop a reliable application.

scholarly journals The Contour Extraction of Cup in Fundus Images for Glaucoma Detection

2016 ◽  
Vol 6 (6) ◽  
pp. 2797
Author(s):  
Anindita Septiarini ◽  
Hamdani Hamdani ◽  
Dyna Marisa Khairina
Keyword(s):  
Feature Extraction ◽  
Extraction Method ◽  
Support Vector ◽  
Fundus Images ◽  
Contour Extraction ◽  
Fundus Image ◽  
Feature Extraction Method ◽  
Glaucoma Detection ◽  
Vector Machines ◽  
The World

<p>Glaucoma is the second leading cause of blindness in the world; therefore the detection of glaucoma is required. The detection of glaucoma is used to distinguish whether a patient's eye is normal or glaucoma. An expert observed the structure of the retina using fundus image to detect glaucoma. In this research, we propose feature extraction method based on cup area contour using fundus images to detect glaucoma. Our proposed method has been evaluated on 44 fundus images consisting of 23 normal and 21 glaucoma. The data is divided into two parts: firstly, used to the learning phase and secondly, used to the testing phase. In order to identify the fundus images including the class of normal or glaucoma, we applied Support Vector Machines (SVM) method. The performance of our method achieves the accuracy of 94.44%.</p>

scholarly journals ANALYSIS OF ALZHEIMER DISEASE PREDICTION USING MACHINE LEARNING TECHNIQUES

2021 ◽  
Vol 9 (1) ◽  
pp. 519-525
Author(s):  
B. Hemalatha, Dr. M. Renukadevi
Keyword(s):  
Machine Learning ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Early Stage ◽  
Machine Learning Algorithms ◽  
Machine Learning Techniques ◽  
Know How ◽  
Positron Emission ◽  
Learning Techniques ◽  
The Many

Alzheimer's Disease (AD) is referred to as one of the highest non-unusual neurodegenerative disorders that inflict eternal harm to the memory-associated brain cells and wonder skills. There is a 99.6 percent failure rate in clinical trials of Alzheimer's disease pills, perhaps due to the fact that AD sufferers cannot be without early-stage complications. This observation analyzed machine learning knowledge of strategies to use empirical statistics to forecast the progression of AD in the years of fate. Diagnosis of AD is often difficult, particularly at an early stage in the disease system, due to the degree of mild cognitive impairment (MCI). However, it is at this point where treatment is much more likely to be successful, so there will be great benefits in enhancing the diagnosis process. Research in this area aims to identify the most complex mechanisms directly related to changes in AD. Various imaging methods are used to diagnose AD, and image modes play a key role in the diagnosis of AD. This paper uses a Positron Emission Tomography (PET) image to detect AD early. The PET image is often used to know how organs and tissues function in the human body. This research study analyses prediction approaches using various kinds of machine learning algorithms to solve AD diagnostic problems. Artificial Neural Networks are one of the many algorithms. Modern research has shown that deep learning is a proficient technique for solving numerous problems of image recognition, but most of these published approaches owe their performance to training on a very large number of data samples.

scholarly journals A Study of Machine Learning Algorithms on Email Spam Classification

10.29007/qshd ◽  
2020 ◽  
Author(s):  
N Sutta ◽  
Z Liu ◽  
X Zhang
Keyword(s):  
Machine Learning ◽  
High Accuracy ◽  
Machine Learning Algorithms ◽  
Machine Learning Techniques ◽  
Spam Detection ◽  
Classification Models ◽  
Detection Techniques ◽  
Learning Techniques ◽  
Comprehensive Comparison ◽  
Email Spam

Despite the fact that different techniques have been developed to filter spam, due to the spammer’s rapid adoption of new spam detection techniques, we are still overwhelmed with spam emails. Currently, machine learning techniques are the most effective ways to classify and filter spam emails. In this paper, a comprehensive comparison and analysis of the performance of various classification models on the 2007 TREC Public Spam Corpus are exhibited in various cases of without or with N- Grams as well as using separate or combined datasets. It is shown that the inclusion of the N-Grams in the pre-processing phase provides high accuracy results for classification models in most of the cases, and the models using the split approach with combined datasets give better results than models using the separate dataset.

scholarly journals Fast COVID-19 and Pneumonia Classification Using Chest X-ray Images

Mathematics ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. 1423
Author(s):  
Juan Eduardo Luján-García ◽  
Marco Antonio Moreno-Ibarra ◽  
Yenny Villuendas-Rey ◽  
Cornelio Yáñez-Márquez
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Respiratory Diseases ◽  
X Ray ◽  
Aggressive Disease ◽  
Learning Techniques ◽  
The World ◽  
Chest X Ray ◽  
The Common ◽  
Deep Learning Model

As of the end of 2019, the world suffered from a disease caused by the SARS-CoV-2 virus, which has become the pandemic COVID-19. This aggressive disease deteriorates the human respiratory system. Patients with COVID-19 can develop symptoms that belong to the common flu, pneumonia, and other respiratory diseases in the first four to ten days after they have been infected. As a result, it can cause misdiagnosis between patients with COVID-19 and typical pneumonia. Some deep-learning techniques can help physicians to obtain an effective pre-diagnosis. The content of this article consists of a deep-learning model, specifically a convolutional neural network with pre-trained weights, which allows us to use transfer learning to obtain new retrained models to classify COVID-19, pneumonia, and healthy patients. One of the main findings of this article is that the following relevant result was obtained in the dataset that we used for the experiments: all the patients infected with SARS-CoV-2 and all the patients infected with pneumonia were correctly classified. These results allow us to conclude that the proposed method in this article may be useful to help physicians decide the diagnoses related to COVID-19 and typical pneumonia.

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