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1.
International Journal of Academic Medicine and Pharmacy ; 4(3):270-274, 2022.
Artigo em Inglês | EMBASE | ID: covidwho-2164775

RESUMO

Background: To evaluate the potential of probiotics in stress management caused by the Covid-19 pandemic. Material(s) and Method(s): PubMed, Elsevier, New England journal of Medicine and Google Scholar were searched for the keywords "Probiotics and stress management during the Covid pandemic" up to 30th April 2022. Result(s): Probiotics have a great potential of managing mild stress. The pandemic has brought about physical as well psychological distress and has had a negative impact on the mental health of individuals. Stress increases the risk of cardiovascular diseases, hypertension and neuropsychiatric disorders. Probiotics can be used to alleviate mental stress. Probiotics maintain ecological balance of gut and provide immunity. They also affect mood and health of host by regulating gut-brain axis of host and may be used as Psychobiotics by altering various neurotransmitters like dopamine, serotonin, adrenocorticotrophic hormone, epinephrine, norepinephrine and GABA. The use of probiotics in mild stress will help reduce the risk of adverse effects and dependence associated with the psychotropic drugs. Conclusion(s): The ongoing studies on probiotics seems to be a good solution towards stress and related problems which is rapidly increasing due to COVID-19 pandemic. Probiotics seem to be beneficial in handling stress as they alter the release of neurotransmitters reducing stress level of an individual and have a positive effect on mood. The current pandemic is likely to continue and there is a need for greater preparedness of stress management, therefore, it is essential to explore the full potential of probiotics application in stress management. Copyright © 2022 Authors.

2.
13th International Conference on Information and Communication Technology Convergence, ICTC 2022 ; 2022-October:1366-1370, 2022.
Artigo em Inglês | Scopus | ID: covidwho-2161411

RESUMO

A report from the World Health Organization reveals that many people lack access to good healthcare services. Primary health care is often inaccessible, not only in developing countries, but also in developed nations like the United States. The lack of sufficient primary care physicians is one of the chief factors contributing to healthcare inaccessibility. Prior research has attempted to address the issue by examining patient symptoms and transcripts through the use of machine learning algorithms, but because numerous illnesses can produce identical symptoms, these efforts have struggled to correctly diagnose and guide patients. We sought to increase the access to healthcare services by utilizing a machine learning system to guide a patient to the appropriate specialist based on the symptoms indicated in their transcripts. In this study, we developed and evaluated an algorithm-based solution that would give the public credible, data-driven, and personalized information about their symptoms, enabling patients and their doctors to make better-educated decisions based on statistics and text transcripts. To do so, we built three models: (1) a transcript model, which uses clinical transcripts to predict the appropriate medical specialist;(2) a keyword model, which uses keyword extraction to reduce noise and isolate the symptoms from the clinical transcripts, and then uses these keywords to predict the appropriate medical specialist;and (3) a COVID-19 risk detection model, which predicts the COVID-19 risk of a patient, something that has not been fully investigated in this field of research. © 2022 IEEE.

3.
Indian Journal of Community Health ; 33(4):568-574, 2021.
Artigo em Inglês | Scopus | ID: covidwho-1675703

RESUMO

Background: Muzzafarnagar Medical College (MMC), Muzzafarnagar was declared a designated covid hospital by the Uttar Pradesh State Government. A Covid Control Room (CCR) was hence established to manage the disaster. Aims & Objectives: The CCR worked as the operational brain of MMC. Study Setting: Muzzafarnagar Medical College, Muzzafarnagar, Uttar Pradesh, India. Study Design: A hospital record based observational study. Material Methods: A total of 1132 admitted covid positive patients in three months constituted the study population. The CCTV cameras were installed inside the isolation wards, and the ICUs with 24/7 video coverage. The DGME (Uttar Pradesh) developed the Patient Information System (PIS) wherein information was uploaded in a database and WhatsApp messages were sent to the relatives twice daily. Results: The CCR received on an average 200 calls per day. A total of 12,622 calls were received in two months. With, PIS in function the no. of calls received in CCR reduced drastically. 100% coverage of the patients’ information was achieved. Conclusion: The scope of the control room has expanded considerably to address various aspects of the covid-19 pandemic crisis. These findings will be helpful as a reference for future. It is one of the first studies and unique in nature. © 2021, Indian Association of Preventive and Social Medicine. All rights reserved.

4.
Proc. Int. Conf. Electron., Commun. Aerosp. Technol., ICECA ; : 1476-1480, 2020.
Artigo em Inglês | Scopus | ID: covidwho-1050280

RESUMO

On the 11th of March 2020, the World Health Organization (WHO) affirmed COVID-19, a pandemic, in response to more than 1,00,000 confirmed cases globally in more than 100 nations and the persistent danger of spreading further. Presently, there's no remedy or vaccine for COVID-19. The only way to curb its menace is taking precautionary measures, as advised by the health experts. Social distancing, that is maintaining a minimum distance of 1 to 1.5 meter between two individuals, is one of the foremost proactive measures advised by WHO. This paper presents a smart wearable device, Suraksha, that can be worn while travelling outside and will help maintain social distancing. The user will be able to rely on this device's alerting mechanism without having to constantly worry about their surroundings. It is a simple device which is easy to use and is built using basic electronic components. The device is also capable of integrating with the health applications over Bluetooth and support contact tracing. © 2020 IEEE.

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