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Hybrid Deep Learning Model to Diagnose Covid-19 on its Early Stages Using Lung CT Images
Published in Ranjeet Kumar Rout, Saiyed Umer, Sabha Sheikh, Amrit Lal Sangal, Artificial Intelligence Technologies for Computational Biology, 2023
K V Kadambari, Lavanya Madhuri Bollipo
December 2019 is the time in which the entire world got struck with the global threat called Corona Virus, a virus which created a drastic impact on nations around the world [12, 4]. With respect to the COVID cases found on Center-for-Systems Science and Engineering (CSSE) present in Johns-Hopkins University [6], many people in 187 different countries over the globe are affected by COVID-19 and so far the death ratio seems to be huge. The symptoms in COVID-19 patients surfaced after 4 to 7 days from the time of virus infection. During this time frame, the affected patients spread the disease to their neighoring persons unknowingly, which resulted in a drastic increase of affection ratio. However, the ratio of symptoms varies according to the climate scenarios as well, such as in American countries the symptoms are noted on 7-day interval and in Asian countries the symptoms are raised in four days. Primarily, the complexity in COVID-19 disease identification is, the properties of virus changes over time and making diagnosis challenging. Thus, there is a need for early detection of COVID-19 disease before the symptom arises in order to reduce the spread of transmission.
Clinical and epidemiological context of COVID-19
Published in Sanjeeva Srivastava, Multi-Pronged Omics Technologies to Understand COVID-19, 2022
Viswanthram Palanivel, Akanksha Salkar, Radha Yadav, Renuka Bankar, Om Shrivastav, Arup Acharjee
The Centers for Disease Control and Prevention (CDC) (Guidance for COVID-19, CDC) has suggested a list of guidelines to limit the spread of person-to-person transmission of the virus. The guidelines of CDC are as follows: (i) To maintain 6 feet physical distance between individuals, (ii) to avoid socializing in public places such as restaurants, bars, fitness centers, theaters, and social gatherings, (iii) to avoid being in poorly ventilated spaces, (iv) to wear a mask or any other protection covering the nose and mouth properly, (v) often washing or sanitizing hands by using alcohol-based sanitizer or hand rub or soap water, (vi) to clean and disinfect the surfaces regularly with sodium hypochlorite or any other disinfectant, (vii) covering nose and mouth with a tissue while sneezing and coughing, (viii) to immediately seek medical attention if having flu-like symptoms, and (ix) to self-isolate or quarantine person with clinical symptoms of COVID-19. Following these guidelines can be an excellent preventive measure for people during these pandemic times. SARS-CoV-2 is highly sensitive to chemicals such as ethanol (75%), ether, and chlorine disinfectants (sodium hypochlorite) and also can be inactivated by ultraviolet radiation and heat treatment at 56°C for 30 minutes (Hoffmann et al. 2021; Li et al. 2020). These measures have been proven to be effective in curbing the spread of SARS-CoV-2.
Role of Artificial Intelligence in COVID-19
Published in Salah-ddine Krit, Vrijendra Singh, Mohamed Elhoseny, Yashbir Singh, Artificial Intelligence Applications in a Pandemic, 2022
S. Lalitha, H. T. Bhavana, K. N. Madhusudhan, Prascheth, Harshitha
Coronavirus disease (COVID-19) is an inflammation infection originated by novel coronavirus. Cold, cough, fever, and loss of smell and taste are general symptoms of COVID-19 and, in critical cases, respiratory problems. It has been declared a worldwide pandemic. The important phases of human life, such as transportation, education, health sector, marketing have been changed due to the attack of COVID-19. Those infected with COVID-19 suffer from respiratory problems but can recovered with proper medical aid. The virus can easily transmit from human to human, hence, it is one of the most dangerous viruses among all virus families. A total of 214 countries have been suffering from this deadly disease. As of September 10, 2020, the worldwide confirmed coronavirus cases numbered 27.5 million, and 894,983 deaths have occurred. The United States had the record for the most cases of COVID-19, nearly 6.3 million confirmed, and 190,856 deaths. Italy, Brazil, India, Spain, and Russia are some other countries that are enormously affected. There are no clinical vaccines available to prevent and no drugs/medical procedures to cure this disease.
Detection of Monkeypox from skin lesion images using deep learning networks and explainable artificial intelligence
Published in Applied Mathematics in Science and Engineering, 2023
Tushar Nayak, Krishnaraj Chadaga, Niranjana Sampathila, Hilda Mayrose, G. Muralidhar Bairy, Srikanth Prabhu, Swathi S. Katta, Shashikiran Umakanth
A multitude of reasons, including physical injury, overexposure to ultraviolet light, infections and tumours, can cause skin lesions [1]. Due to the rashes being on the skin, non-invasive techniques such as imaging can be used as a diagnostic modality for certain diseases that cause skin lesions using machine learning and deep learning [2]. These algorithms pick up unique features of skin lesions that might be difficult for humans to identify. The usage of deep learning-based classifiers has been very popular due to the increased computational power of computers and the public availability of data sets and information to train convolutional neural networks. Fatal diseases such as COVID-19 prompted the development of alternate diagnostic modalities due to the high transmission rate of the disease [3]. Common symptoms of COVID-19 include fever, cough, and fatigue, among others. These symptoms were similar to Influenza (flu), which further complicated and increased the number of people that needed to be tested. Digital images of X-Ray and Computer Tomography (CT) scans were used to non-invasively detect coronavirus patients showing symptoms of general respiratory diseases, alongside RT–PCR tests to identify the same infection using nose and throat swabs [4].
Application of Artificial Intelligence on Post Pandemic Situation and Lesson Learn for Future Prospects
Published in Journal of Experimental & Theoretical Artificial Intelligence, 2023
Priyanka Dwivedi, Achintya Kumar Sarkar, Chinmay Chakraborty, Monoj Singha, Vineet Rojwal
Moreover, cough, sore throat, runny nose, and breath rates are also reflecting the symptoms of COVID-19 positive. They affect the person’s voice (due to the infection in their voice production system) with respect to the normal condition. Therefore, speech analysis/audio-processing techniques (Schuller et al., 2020) can be utilised to capture this relevant information for building a COVID-19 detection system, where spectrogram of COVID-19 infected and non-infected subjects’ voice/speech can be used for training the DNNs analogous to the lung image-based system. Since voice-based systems are a non-invasive method, they can be explored via a simple phone call or sending the recording voice of a person using the mobile device to the server (cloud). In addition, a person does not need to visit the hospital personally. Besides, the fusion of the different COVID-19 detection systems using various supervised learning methods could be an advantage in the post-COVID-19 analysis as they can carry complementary information for others to improve the overall detection. For fusion (Fellner et al., 2006), a development dataset is required to train the fusion algorithm, so a large amount of post-COVID-19 available data is the ideal choice for building a robust fusion system.
Protective role of physical activity patterns prior to COVID-19 confinement with the severity/duration of respiratory pathologies consistent with COVID-19 symptoms in Spanish populations
Published in Research in Sports Medicine, 2023
Pedro Ángel Latorre-Román, Iris Paola Guzmán-Guzmán, Pedro Delgado-Floody, Julio Herrador Sanchez, Jerónimo Aragón-Vela, Felipe García Pinillos, Juan A. Párraga Montilla
Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), originated in Wuhan, China in December 2019, and on 11 March 2020, the World Health Organization (WHO) (World Health Organisation, 2020) declared the outbreak a pandemic. Most people infected with the SARS-CoV-2 virus will experience mild to moderate respiratory illness and recover without requiring special treatment. Older people and those with underlying medical problems such as cardiovascular disease, diabetes, chronic respiratory disease and cancer, however, are more likely to develop serious illnesses. The most common symptoms of COVID-19 are fever, dry cough and fatigue. Other, less common symptoms that may affect patients include aches and pains, nasal congestion, headache, conjunctivitis, sore throat, diarrhoea, loss of taste or smell, skin rash and discoloration of the fingers or toes.