A Proposal of Building an Early-Stage Diagnosis System of First-Aid through Wireless Internet

2008 ◽  
Author(s):  
Randy S. Tolentino ◽  
Jung-Hwan Hwang ◽  
Sun-Ho Kim ◽  
Yong-Tae Kim ◽  
Gil-Cheol Park ◽  
...  
Keyword(s):  
Early Stage ◽  
First Aid ◽  
Wireless Internet ◽  
Diagnosis System

scholarly journals CNN-based Diagnosis System on Skin Cancer using Ensemble Method Weighted by Cubic Precision

2021 ◽  
Author(s):  
Pengcheng Jiang
Keyword(s):  
User Interface ◽  
Skin Cancer ◽  
Language Processing ◽  
Classification Accuracy ◽  
Model Updating ◽  
Early Stage ◽  
Model Performance ◽  
Diagnosis System ◽  
Cancer Symptoms ◽  
User Friendly

<i>Abstract</i>— One of the most prevalent diseases, skin cancer, has been proven to be treatable at an early stage. Thus, techniques that allow individuals to identify skin cancer symptoms early are in great demand. This paper proposed an interactive skin lesion diagnosis system based on the ensemble of multiple sophisticated CNN models for image classification. The performance of ResNet50, ResNeXt50, ResNeXt101, EfficientNetB4, Mobile-NetV2, MobileNetV3, and MnasNet are investigated separately as ensemble components. Then, using various criteria, we constructed ensembles and compared the accuracy they achieved. Moreover, we designed a method to update the ensemble for new data and examined its performance. In addition, a few natural language processing (NLP) techniques were used to make our system more user-friendly. To integrate all the functionalities, we built a user interface with PyQt5. As a result, MobileNetV3 achieved 91.02% as the best accuracy among all single models; ensemble weighted by cubic precision achieved 92.84% accuracy as the highest one in this study; a notable improvement in accuracy demonstrated the effectiveness of the model updating approach, and a system with all of the desired features was successfully developed. These findings benefit in two aspects. For model performance, applying cubic precisions can increase ensemble learning classification accuracy. For the developed diagnosis system, it can aid in the

scholarly journals A Personalized Computer-Aided Diagnosis System for Mild Cognitive Impairment (MCI) Using Structural MRI (sMRI)

Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5416
Author(s):  
Fatma El-Zahraa A. El-Gamal ◽  
Mohammed Elmogy ◽  
Ali Mahmoud ◽  
Ahmed Shalaby ◽  
Andrew E. Switala ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Neurodegenerative Disorder ◽  
Early Stage ◽  
Brain Regions ◽  
Computer Aided Diagnosis ◽  
Cortical Region ◽  
Diagnosis System ◽  
Computer Aided ◽  
Aided Diagnosis

Alzheimer’s disease (AD) is a neurodegenerative disorder that targets the central nervous system (CNS). Statistics show that more than five million people in America face this disease. Several factors hinder diagnosis at an early stage, in particular, the divergence of 10–15 years between the onset of the underlying neuropathological changes and patients becoming symptomatic. This study surveyed patients with mild cognitive impairment (MCI), who were at risk of conversion to AD, with a local/regional-based computer-aided diagnosis system. The described system allowed for visualization of the disorder’s effect on cerebral cortical regions individually. The CAD system consists of four steps: (1) preprocess the scans and extract the cortex, (2) reconstruct the cortex and extract shape-based features, (3) fuse the extracted features, and (4) perform two levels of diagnosis: cortical region-based followed by global. The experimental results showed an encouraging performance of the proposed system when compared with related work, with a maximum accuracy of 86.30%, specificity 88.33%, and sensitivity 84.88%. Behavioral and cognitive correlations identified brain regions involved in language, executive function/cognition, and memory in MCI subjects, which regions are also involved in the neuropathology of AD.

Early Stage Breast Cancer Detection Using Wearable Health Diagnosis System

2021 ◽  
Vol 11 (12) ◽  
pp. 3038-3043
Author(s):  
S. M. Asha Banu ◽  
K. Meena Alias Jeyanthi
Keyword(s):  
Breast Cancer ◽  
Cancer Cells ◽  
Early Breast Cancer ◽  
Early Stage ◽  
Effective Permittivity ◽  
Diagnosis System ◽  
Textile Antenna ◽  
Cancer Tissues ◽  
Bio Compatibility ◽  
Health Diagnosis

The most prevalent cancer that threatens women’s life is Breast cancer. According to WHO Statistics in 2020, 2.3 Million Women were diagnosed with Breast cancer and 685000 death rate were disclosed globally. In this paper, Wearable Health Diagnosis System (WHDS) based antenna for the identification of the early breast cancer is discussed. Conventional methods are limited by their uncomfortable testing setups, panic environment and failure in results. Recently, textile based antenna for microwave imaging stared to work on the detection of the cancer cells at the earlier stage in breast. WHDS antenna has the requirements of wider bandwidth, high resolution, low Specific Absorption Rate (SAR), bio compatibility, and flexibility. The proposed work is based on the textile antenna using Denim substrate (permittivity = 1.67, thickness = 2 mm) to diagnosis the Early Breast Cancer Tissues (EBCT). Using the following antenna parameters (return loss, E-filed, H-field and SAR values), the position and malignancy of the EBCT is identified. Since the dielectric properties of the cancer cells are high, the influence of the effective permittivity is higher on the E-field and SAR. Along with the above parameters, comparison of various substrate materials (Denim, FR4, and RT duroid) were also tested and Denim is selected for our application as it introduces greater reflection co-efficient and wider bandwidth. The proposed antenna is designed to operate at a frequency of 2–4 GHz. This miniaturised antenna has a volume of 30 × 28 × 2 mm3.

scholarly journals CNN-based Diagnosis System on Skin Cancer using Ensemble Method Weighted by Cubic Precision

2021 ◽  
Author(s):  
Pengcheng Jiang
Keyword(s):  
User Interface ◽  
Skin Cancer ◽  
Language Processing ◽  
Classification Accuracy ◽  
Model Updating ◽  
Early Stage ◽  
Model Performance ◽  
Diagnosis System ◽  
Cancer Symptoms ◽  
User Friendly

<i>Abstract</i>— One of the most prevalent diseases, skin cancer, has been proven to be treatable at an early stage. Thus, techniques that allow individuals to identify skin cancer symptoms early are in great demand. This paper proposed an interactive skin lesion diagnosis system based on the ensemble of multiple sophisticated CNN models for image classification. The performance of ResNet50, ResNeXt50, ResNeXt101, EfficientNetB4, Mobile-NetV2, MobileNetV3, and MnasNet are investigated separately as ensemble components. Then, using various criteria, we constructed ensembles and compared the accuracy they achieved. Moreover, we designed a method to update the ensemble for new data and examined its performance. In addition, a few natural language processing (NLP) techniques were used to make our system more user-friendly. To integrate all the functionalities, we built a user interface with PyQt5. As a result, MobileNetV3 achieved 91.02% as the best accuracy among all single models; ensemble weighted by cubic precision achieved 92.84% accuracy as the highest one in this study; a notable improvement in accuracy demonstrated the effectiveness of the model updating approach, and a system with all of the desired features was successfully developed. These findings benefit in two aspects. For model performance, applying cubic precisions can increase ensemble learning classification accuracy. For the developed diagnosis system, it can aid in the

scholarly journals First aid and rescue of a critically injured person at 5,700 m

2020 ◽  
Vol 71 (11-12) ◽  
pp. 300-304
Author(s):  
M Tannheimer
Keyword(s):  
Early Stage ◽  
First Aid ◽  
External Support ◽  
Stressful Situation ◽  
Rescue Operation ◽  
Intensive Training ◽  
Mountain Rescue ◽  
Injured Person ◽  
Long Time ◽  
High Level

Accidents during mountaineering are special because mountain rescue operations are time-consuming and material-intensive. Since even in Europe it takes a long time for professional help to reach the injured person, first aid rugulary has to be provided by the accompanying mountaineers. This case report of a seriously injured person at an altitude of 5,700 m describes the special challenges of such a rescue operation. After the accident, the patient has to be moved out of the immediate danger zone to enable examination, treatment must be startet and further transport organized. This requires profound training in makeshift mountain rescue techniques, the use of diagnostic algorithms and safe application of medications. Generally, material and manpower are very limited in such situations and exhaustion due to the challenging tour is an aggravating factor. Therefore, the group has to look for external help and support at an early stage. For this purpose, efficient communication equipment is required and contacts must already be established. There is a high level of emotional stress when treating friends. In order to cope successfully with such a stressful situation, profound education and intensive training, as well as a strategy for external support developed in advance, are necessary. Key Words: Mountain Rescue, Traumatic Brain Injury, S-Ketamine, Remote Area, Wilderness Medicine

scholarly journals The knowledge of teachers as a key factor in providing first aid in primary schools

2019 ◽  
Vol 5 (1) ◽  
pp. 17-29
Author(s):  
Uroš Kovačič ◽  
Amela Lozić ◽  
Damjan Slabe ◽  
Andrej Starc
Keyword(s):  
General Education ◽  
Primary School ◽  
Primary Schools ◽  
Early Stage ◽  
First Aid ◽  
Living Environment ◽  
Theoretical Knowledge ◽  
Survey Questionnaire ◽  
Educational Role ◽  
Key Factor

Background: In addition to home, school is the second most important living environment in a child’s life. Injuries that most often occur in school and on the school playground are the primary cause for the death of children. In case of sudden health problems in schools, teachers are usually the first to be at a child’s side. We were interested in how well teachers in primary schools are familiar with first aid measures in selected health cases. Methods: Collecting of data in the framework of the descriptive method of research was conducted with an anonymous survey questionnaire using the online program 1ka. One hundred and ninety-two teachers filled in the survey questionnaire in its entirety. Results: Teachers have a lack of theoretical knowledge of first aid in life-threatening situations. In four of the nine questions on the selected first aid measures, the teachers who teach at the upper level of primary school showed statistically significantly poorer knowledge compared to the teachers who teach at the lower level of primary school. Conclusions: Teachers at the lower level who teach in the early stage of the education system displayed better theoretical knowledge of first aid. This may be the result of a difference in their educational role during the schooling of an individual pupil. While a lower-level teacher who is associating with the particular pupil all day long is involved in the general education of the pupil, the teacher at a higher-level teaches a specific subject and only has contact with a certain pupil a few hours a week. Theoretical knowledge is only a basic prerequisite for performing first aid, practical skills are required as well. It is essential that teachers in primary school renew and upgrade their knowledge of first aid, as doctrinal guidance changes and first aid knowledge is also forgotten. If teachers are responsible for the practical performance of first aid measures on an injured or suddenly ill child, the school principals are responsible for ensuring the conditions for the implementation of these measures, including the provision of training for their employees.

scholarly journals A symmetry based anomaly detection in brain using cellular automata for computer aided diagnosis

2018 ◽  
Vol 14 (1) ◽  
pp. 471
Author(s):  
Nisha V M ◽  
L Jeganathan
Keyword(s):  
Cellular Automata ◽  
Early Stage ◽  
Computer Aided Diagnosis ◽  
Brain Images ◽  
Cellular Automata Model ◽  
Computing Power ◽  
Diagnosis System ◽  
Proposed Model ◽  
Computer Aided ◽  
Aided Diagnosis

Computer aided diagnosis (CAD) is an advancing technology in medical imaging. CAD acts as an additional computing power for doctors to interpret the medical images which leads to a more accurate diagnosis of the disease.CAD system increases the chances of detection of brain lesions by assisting the physicians in decreasing the observational oversight in the early stage of diseases.This paper focuses on the development of a cellular automata based model to find the anomaly prone areas in human brains.Because of the bilateral symmetric nature of human brain, a symmetry based cellular automata model is proposed.An algorithm is designed based on the proposed model to detect the anomaly prone areas in brain images. The proposed model can be a standalone model or it can be incorporated to a sophisticated computer aided diagnosis system. By incorporating asymmetry information into a computer aided diagnosis system, enhances its performance in identifying the anomalies exists in bilaterally symmetrical brain images.

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