Study Of Deep Learning Techniques For Differently Abled Applications And Detection Techniques

In worldwide, Visually Impaired Persons (VIP) are facing several issue related to visual impairment and blindness and they are assisted with technical inventions. Based on the survey from World Health Organization (WHO), around 2.2 billion peoples are suffered from visual impairment and among them 1 million peoples are suffered by blindness. Vision is the major sensing organ of the human and to assist the VIP regarding this, there are various digital vision products are in the market which is based on digital technologies and advanced algorithms. This will transform the VIP’s vision world into audio to get to know about their surroundings includes objects, motion, obstacles and spatial locations. The objective of this paper is to provide the detailed survey about the existing object recognition, face recognition and text to voice recognition methods proposed to assist VIP. Due to the increase development of machine learning and deep learning algorithms, the digital image recognition and object recognition are become more efficient. These advanced technologies can make sure to assist the VIP to detect and recognize the people face and objects in front of them in the form of audio that are practiced by them on daily basis.

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The relevance of dietetic approach of Ayurveda from the perspective of COVID-19 pandemic

International Journal of Research in Pharmaceutical Sciences ◽

10.26452/ijrps.v11ispl1.3077 ◽

2020 ◽

Vol 11 (SPL1) ◽

pp. 748-752

Author(s):

Swapnali Khabade ◽

Bharat Rathi ◽

Renu Rathi

Keyword(s):

Severe Acute Respiratory Syndrome ◽

Healthy Person ◽

World Health ◽

Physical And Mental Health ◽

Leading Role ◽

Global Pandemic ◽

The People ◽

The World ◽

Health Organization ◽

The Individual

A novel, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), causes severe acute respiratory syndrome and spread globally from Wuhan, China. In March 2020 the World Health Organization declared the SARS-Cov-2 virus as a COVID- 19, a global pandemic. This pandemic happened to be followed by some restrictions, and specially lockdown playing the leading role for the people to get disassociated with their personal and social schedules. And now the food is the most necessary thing to take care of. It seems the new challenge for the individual is self-isolation to maintain themselves on the health basis and fight against the pandemic situation by boosting their immunity. Food organised by proper diet may maintain the physical and mental health of the individual. Ayurveda aims to promote and preserve the health, strength and the longevity of the healthy person and to cure the disease by properly channelling with and without Ahara. In Ayurveda, diet (Ahara) is considered as one of the critical pillars of life, and Langhana plays an important role too. This article will review the relevance of dietetic approach described in Ayurveda with and without food (Asthavidhi visheshaytana & Lanhgan) during COVID-19 like a pandemic.

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ARIMA model for forecasting COVID-19 Death cases in India (Preprint)

10.2196/preprints.24107 ◽

2020 ◽

Author(s):

Jeya Sutha M

Keyword(s):

Arima Model ◽

Public Health Emergency ◽

World Health ◽

The People ◽

The World ◽

The Status ◽

The Government ◽

Health Organization ◽

Spread Of Infection ◽

Death Cases

UNSTRUCTURED COVID-19, the disease caused by a novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a highly contagious disease. On January 30, 2020 the World Health Organization declared the outbreak as a Public Health Emergency of International Concern. As of July 25, 2020; 15,947,292 laboratory-confirmed and 642,814 deaths have been reported globally. India has reported 1,338,928 confirmed cases and 31,412 deaths till date. This paper presents different aspects of COVID-19, visualization of the spread of infection and presents the ARIMA model for forecasting the status of COVID-19 death cases in the next 50 days in order to take necessary precaution by the Government to save the people.

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World Health Report on Vision: Aging Implications for Global Vision and Eye Health

Innovation in Aging ◽

10.1093/geroni/igaa057.2933 ◽

2020 ◽

Vol 4 (Supplement_1) ◽

pp. 807-808

Author(s):

Bonnielin Swenor ◽

Varshini Varadaraj ◽

Moon Jeong Lee ◽

Heather Whitson ◽

Pradeep Ramulu

Keyword(s):

Older Adults ◽

Visual Impairment ◽

Vision Loss ◽

World Health ◽

World Health Report ◽

Global Public Health ◽

Eye Care ◽

Health Report ◽

Public Health Challenges ◽

Health Organization

Abstract In 2019, the World Health Organization World Report on Vision estimated that that 2.2 billion people have a vision impairment, of which almost half could have been prevented or is yet to be addressed. As the global population ages and the prevalence of visual impairment increases, inequities in eye care and the downstream health and aging consequences of vision loss will become magnified. This session will: (1) provide key information regarding the burden of eye disease and visual impairment among older adults worldwide; (2) outline a framework created to conceptualize the aging and long-term health implications of vision loss, and (3) discuss the global public health challenges to eye care and to maximizing health for older adults with visual impairments.

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IoT and Deep Learning Based Approach for Rapid Screening and Face Mask Detection for Infection Spread Control of COVID-19

Applied Sciences ◽

10.3390/app11083495 ◽

2021 ◽

Vol 11 (8) ◽

pp. 3495

Author(s):

Shabir Hussain ◽

Yang Yu ◽

Muhammad Ayoub ◽

Akmal Khan ◽

Rukhshanda Rehman ◽

...

Keyword(s):

Deep Learning ◽

Low Cost ◽

Face Mask ◽

World Health ◽

Rapid Screening ◽

Screening System ◽

Source Of Infection ◽

The Face ◽

Health Organization ◽

Vaccine Distribution

The spread of COVID-19 has been taken on pandemic magnitudes and has already spread over 200 countries in a few months. In this time of emergency of COVID-19, especially when there is still a need to follow the precautions and developed vaccines are not available to all the developing countries in the first phase of vaccine distribution, the virus is spreading rapidly through direct and indirect contacts. The World Health Organization (WHO) provides the standard recommendations on preventing the spread of COVID-19 and the importance of face masks for protection from the virus. The excessive use of manual disinfection systems has also become a source of infection. That is why this research aims to design and develop a low-cost, rapid, scalable, and effective virus spread control and screening system to minimize the chances and risk of spread of COVID-19. We proposed an IoT-based Smart Screening and Disinfection Walkthrough Gate (SSDWG) for all public places entrance. The SSDWG is designed to do rapid screening, including temperature measuring using a contact-free sensor and storing the record of the suspected individual for further control and monitoring. Our proposed IoT-based screening system also implemented real-time deep learning models for face mask detection and classification. This module classified individuals who wear the face mask properly, improperly, and without a face mask using VGG-16, MobileNetV2, Inception v3, ResNet-50, and CNN using a transfer learning approach. We achieved the highest accuracy of 99.81% while using VGG-16 and the second highest accuracy of 99.6% using MobileNetV2 in the mask detection and classification module. We also implemented classification to classify the types of face masks worn by the individuals, either N-95 or surgical masks. We also compared the results of our proposed system with state-of-the-art methods, and we highly suggested that our system could be used to prevent the spread of local transmission and reduce the chances of human carriers of COVID-19.

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Leading causes of blindness and visual impairment in the region of Eastern Herzegovina

Medicinski pregled ◽

10.2298/mpns0602015c ◽

2006 ◽

Vol 59 (1-2) ◽

pp. 15-18 ◽

Cited By ~ 1

Author(s):

Lala Ceklic ◽

Slobodanka Latinovic ◽

Petar Aleksic

Keyword(s):

Visual Impairment ◽

Visually Impaired ◽

Age Distribution ◽

Epidemiological Studies ◽

Population Based ◽

World Health ◽

Visual Disability ◽

Common Causes ◽

Health Organization ◽

Blind Persons

Introduction. Visual impairment and blindness are serious social and health problems in the world. 1992 classification of visual disorders by World Health Organization has recently been implemented. The goal of this study was to determine common causes of visual impairment and blindness in the region of Eastern Herzegovina. Material and methods. In this population based study we have analyzed medical records stored in the regional Association of Visually Impaired and Blind Persons of the Republic of Srpska (Trebinje, Bileca, Foca, Eastern Sarajevo). The analysis included sex and age distribution of registered population, classification and leading causes of visual disability and blindness. Results. There are 298 registered persons with visual disability and blindness in the region of Eastern Herzegovina and Eastern Sarajevo. The prevalence of visual impairment and blindness in the aforementioned region is 0.1%. Among the studied population, there are more males than females with visual disability or blindness (56% versus 44%). Most (78%) of registered persons are blind, and only 22% are visually impaired. 43% of registered population are in the IV category and only 8.38% are registered in the II category. Only 2% of registered population are children. Common causes of visual disability and blindness in the region of Eastern Herzegovina are: glaucoma (22%), cataract (17%), myopia alta (13%), diabetic retinopathy (12%) and ocular trauma (11%). Common causes of children's visual impairment include: optic nerve anomalies, congenital cataract and premature retinopathy. Discussion and conclusion Compared with literature data, common causes of blindness and visual impairment in the region of Eastern Herzegovina do not differ significantly from those in other regions. Registration is based on the WHO model, but it is possible only by performing active epidemiological studies. .

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Mental Health

Research Anthology on Mental Health Stigma, Education, and Treatment ◽

10.4018/978-1-7998-8544-3.ch009 ◽

2021 ◽

pp. 143-152

Author(s):

Shazia Ali ◽

Amat Us Samie ◽

Asma Ali ◽

Aashiq Hussain Bhat ◽

Tariq Mir ◽

...

Keyword(s):

Mental Health ◽

Political Conflict ◽

World Health ◽

Global Burden ◽

Age Group ◽

Health Issues ◽

The People ◽

Working Age ◽

War And Conflict ◽

Health Organization

Global health issues are a global burden and are relatively common in industrialized societies. The World Health Organization and researchers have developed and rebuilt tools to report the burden of disease affecting mortality and health of the people. Apart from America and Europe, which are at an average of global burden for mental health disease, in some regions it is a major priority to be addressed globally. In South East Asia, one of the affected regions is Kashmir, Northern Indian. Disasters have manifested in various forms encompassing the natural calamities of earthquake, flood, landslides and manmade calamities of violence. Trauma due to manmade calamities has taken over as a leading cause of morbidity and mortality among the most productive working age group of 12-35 years. The chapter aims to understand the patterns of resilience in people surviving war and conflict in Kashmir over last 60 years. The focus is on the young population of society. Generations in Kashmir have faced the psychosocial impact of ongoing political conflict since the 1980's.

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Mental Health

Biopsychosocial Perspectives and Practices for Addressing Communicable and Non-Communicable Diseases - Advances in Medical Diagnosis, Treatment, and Care ◽

10.4018/978-1-7998-2139-7.ch002 ◽

2020 ◽

pp. 18-29

Author(s):

Shazia Ali ◽

Amat Us Samie ◽

Asma Ali ◽

Aashiq Hussain Bhat ◽

Tariq Mir ◽

...

Keyword(s):

Mental Health ◽

Political Conflict ◽

World Health ◽

Global Burden ◽

Age Group ◽

Health Issues ◽

The People ◽

Working Age ◽

War And Conflict ◽

Health Organization

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Development of the Troponin Detection System Based on the Nanostructure

Micromachines ◽

10.3390/mi10030203 ◽

2019 ◽

Vol 10 (3) ◽

pp. 203 ◽

Cited By ~ 5

Author(s):

Taek Lee ◽

Jae-Hyuk Ahn ◽

Jinha Choi ◽

Yeonju Lee ◽

Jin-Myung Kim ◽

...

Keyword(s):

Detection System ◽

Surface Enhanced Raman Spectroscopy ◽

The Body ◽

World Health ◽

Detection Techniques ◽

Number Of Patients ◽

Creatine Kinase Mb ◽

High Death ◽

Surface Enhanced Raman ◽

Health Organization

During the last 30 years, the World Health Organization (WHO) reported a gradual increase in the number of patients with cardiovascular disease (CVD), not only in developed but also in developing countries. In particular, acute myocardial infarction (AMI) is one of the severe CVDs because of the high death rate, damage to the body, and various complications. During these harmful effects, rapid diagnosis of AMI is key for saving patients with CVD in an emergency. The prompt diagnosis and proper treatment of patients with AMI are important to increase the survival rate of these patients. To treat patients with AMI quickly, detection of a CVD biomarker at an ultra-low concentration is essential. Cardiac troponins (cTNs), cardiac myoglobin (cMB), and creatine kinase MB are typical biomarkers for AMI detection. An increase in the levels of those biomarkers in blood implies damage to cardiomyocytes and thus is related to AMI progression. In particular, cTNs are regarded as a gold standard biomarker for AMI diagnosis. The conventional TN detection system for detection of AMI requires long measurement time and is labor-intensive and tedious. Therefore, the demand for sensitive and selective TN detection techniques is increasing at present. To meet this demand, several approaches and methods have been applied to develop a TN detection system based on a nanostructure. In the present review, the authors reviewed recent advances in TN biosensors with a focus on four detection systems: (1) An electrochemical (EC) TN nanobiosensor, (2) field effect transistor (FET)-based TN nanobiosensor, (3) surface plasmon resonance (SPR)-based TN nanobiosensor and (4) surface enhanced Raman spectroscopy (SERS)-based TN nanobiosensor.

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A Review on a Deep Learning Perspective in Brain Cancer Classification

Cancers ◽

10.3390/cancers11010111 ◽

2019 ◽

Vol 11 (1) ◽

pp. 111 ◽

Cited By ~ 38

Author(s):

Gopal S. Tandel ◽

Mainak Biswas ◽

Omprakash G. Kakde ◽

Ashish Tiwari ◽

Harman S. Suri ◽

...

Keyword(s):

Deep Learning ◽

Brain Cancer ◽

Cost Effective ◽

World Health ◽

Imaging Modalities ◽

Computer Assisted ◽

Learning Paradigm ◽

Brain Scans ◽

Magnetic Resonance Imaging Mri ◽

Health Organization

A World Health Organization (WHO) Feb 2018 report has recently shown that mortality rate due to brain or central nervous system (CNS) cancer is the highest in the Asian continent. It is of critical importance that cancer be detected earlier so that many of these lives can be saved. Cancer grading is an important aspect for targeted therapy. As cancer diagnosis is highly invasive, time consuming and expensive, there is an immediate requirement to develop a non-invasive, cost-effective and efficient tools for brain cancer characterization and grade estimation. Brain scans using magnetic resonance imaging (MRI), computed tomography (CT), as well as other imaging modalities, are fast and safer methods for tumor detection. In this paper, we tried to summarize the pathophysiology of brain cancer, imaging modalities of brain cancer and automatic computer assisted methods for brain cancer characterization in a machine and deep learning paradigm. Another objective of this paper is to find the current issues in existing engineering methods and also project a future paradigm. Further, we have highlighted the relationship between brain cancer and other brain disorders like stroke, Alzheimer’s, Parkinson’s, and Wilson’s disease, leukoriaosis, and other neurological disorders in the context of machine learning and the deep learning paradigm.

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An Explainable approach to Deep Learning from CT-scans for Covid Identification

10.36227/techrxiv.15135846.v1 ◽

2021 ◽

Author(s):

Eduardo Soares ◽

Plamen Angelov ◽

Ziyang Zhang

Keyword(s):

Deep Learning ◽

World Health ◽

Learning Approaches ◽

Heat Map ◽

Algorithm Performance ◽

Decision Mechanism ◽

The World ◽

Public Health Officials ◽

Decision Structure ◽

Health Organization

The Covid-19 disease has spread widely over the whole world since the beginning of 2020. Following the epidemic which started in Wuhan, China on January 30, 2020 the World Health Organization (WHO) declared a global health emergency and a pandemic. Researchers of different disciplines work along with public health officials to understand the SARS-CoV-2 pathogenesis and jointly with the policymakers urgently develop strategies to control the spread of this new disease. Recent findings have observed specific image patterns from computed tomography (CT) for patients infected by SARS-CoV-2 which are distinct from the other pulmonary diseases. In this paper, we propose an explainable-by-design that has an integrated image segmentation mechanism based on SLIC that improves the algorithm performance and the interpretability of the resulting model. In order to evaluate the proposed approach, we used the SARS-CoV-2 CT scan dataset that we published recently and has been widely used in the literature. The proposed Super-xDNN could obtain statistically better results than traditional deep learning approaches as DenseNet-201 and Resnet-152. Furthermore, it also improved the explainability and interpretability of its decision mechanism when compared with the xDNN basis approach that uses the whole image as prototype. The segmentation mechanism of Super-xDNN favored a decision structure that is more close to the human logic. Moreover, it also allowed the provision of new insights as a heat-map which highlights the areas with highest similarities with Covid-19 prototypes, and an estimation of the area affected by the disease.

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