Investigating Diabetic Subjects on Their Correlation With TTH and CAD

2020 ◽  
pp. 197-220
Author(s):  
Rohit Rastogi ◽  
Devendra K. Chaturvedi ◽  
Parul Singhal ◽  
Mayank Gupta
Keyword(s):  
Public Health ◽  
Artificial Intelligence ◽  
Big Data ◽  
Digital Technologies ◽  
Public Health Problem ◽  
Major Public Health Problem ◽  
Quality Patient Care ◽  
Life Threatening ◽  
Natural Information ◽  
Digital Healthcare

Digital technology is modernizing healthcare. Large volumes of data refer to big data by digitising health information that can quickly be processed by machines. Digital healthcare analysis is the ability to diagnose and suggest ways to reduce costs; provide quality patient care and outcomes, available 24/7; reach to patients located in vast distant geographical areas; and avert preventable diseases. Artificial intelligence (AI) is an autonomous real-time machine system in comparison to natural information analyzed by humans. Diabetes is a serious, under-reported, life-threatening disease affecting millions of people of all ages, and researchers have identified it to be a major public health problem that is approaching epidemic proportions globally. The purpose of this study is to investigate diabetes analysis from CAD and other diseases using the latest advanced digital technologies to analyze information extracted from IoT and big data and stress correlation (TTH) on human health.

scholarly journals Modeling Obesity and Its Associated Disorders in Drosophila

Physiology ◽  
2013 ◽  
Vol 28 (2) ◽  
pp. 117-124 ◽  
Author(s):  
Irene Trinh ◽  
Gabrielle L. Boulianne
Keyword(s):  
Public Health ◽  
Heart Disease ◽  
Environmental Factors ◽  
Health Problem ◽  
Public Health Problem ◽  
Major Public Health Problem ◽  
Complex Disorder ◽  
Gene Environment ◽  
Life Threatening ◽  
Genetic And Environmental Factors

In recent years, obesity has been recognized as a major public health problem due to its increased prevalence in both children and adults and its association with numerous life-threatening complications including diabetes, heart disease, hypertension, and cancer. Obesity is a complex disorder that is the result of the interaction between predisposing genetic and environmental factors. However, the precise nature of these gene-gene and gene-environment interactions remains unclear. Here, we will describe recent studies demonstrating how fruit flies can be used to identify and characterize the mechanisms underlying obesity and to establish models of obesity-associated disorders.

scholarly journals Editorial for the Special Issue: Epidemiology, Transmission, Cell Biology and Pathogenicity of Cryptosporidium

2021 ◽  
Vol 9 (3) ◽  
pp. 511
Author(s):  
Gabriela Certad ◽  
Eric Viscogliosi
Keyword(s):  
Public Health ◽  
Health Problem ◽  
Cell Biology ◽  
Public Health Problem ◽  
Apicomplexan Parasite ◽  
Major Public Health Problem ◽  
Special Issue ◽  
Life Threatening ◽  
Immunocompromised Hosts

The apicomplexan parasite Cryptosporidium represents a major public health problem in humans and animals by causing self-limited diarrhea in immunocompetent individuals and life-threatening disease in immunocompromised hosts [...]

scholarly journals A critical review on vrischika visha W.S.R. to keraliya visha chikitsa

2021 ◽  
Vol 12 (2) ◽  
pp. 1162-1167
Author(s):  
Shanti R Nair ◽  
Suwarna Meshram ◽  
Prasanth R Krishnan
Keyword(s):  
Public Health ◽  
Older Adults ◽  
Public Health Problem ◽  
Treatment Modalities ◽  
Medical Attention ◽  
Major Public Health Problem ◽  
Scorpion Sting ◽  
Life Threatening ◽  
Scorpion Stings ◽  
Specific Symptoms

Scorpion stings are major public health problem especially in rural parts of India. Envenomation from Scorpions if estimating on yearly basis it is about 12 lakh people per year and is responsible for nearly about 3250 deaths. There are about 1400 species of scorpions identified worldwide out of this only 53 are reported to be dangerous to humans, In India we have identified around 86 species. Poison due to insect bite is common and can be accompanied with a variety of symptoms ranging from simple itching to life threatening situations. Many may go through minor problems like swelling, tingling or numbness due to the sting. Scorpion sting usually results in severe symptoms, as its venom is more potent. Young children and older adults may require immediate treatment. Vrischikadamsha is such a specific envenomation that requires medical attention. There are ample references treatment modalities and medicines in Keraleeyavisha chikitsa granthas and ayurvedic classics which are described for managing vrischikavisha. Many of the keraliyavishagrantha are written in Malayalam hence there is a need to explore and bring out the remedies. So in this article a humble effort is made to bring out the different vrischika and treatment modalities described in keraleeyagrandhas along with the specific symptoms.

scholarly journals SOME CHARACTERISTICS OF ENTREPRENEURSHIP IN MEDICINE. THE DIGITALIZATION OF THE MEDICAL SYSTEM IN ROMANIA

2021 ◽  
Vol 70 (2) ◽  
pp. 99-102
Author(s):  
Irina Dijmărescu ◽  
◽  
Keyword(s):  
Public Health ◽  
Artificial Intelligence ◽  
Cloud Computing ◽  
Big Data ◽  
Healthcare System ◽  
Digital Technologies ◽  
Medical System ◽  
Continuous Growth ◽  
Collaboration Platforms ◽  
Complex Methods

Entrepreneurship and medicine are in continuous growth alongside, and even if they appear to be completely different fields, entrepreneurship in medicine is becoming of remarkable interest, further highlighted by the COVID-19 pandemic. A main reason for this is its ability to use digital technologies, which are meant to improve healthcare. Applying digitalization in healthcare includes not only computer and database use (cloud computing, big data), but more complex methods such as robotics, automation, internet of things, artificial intelligence and, not lastly, collaboration platforms. Some shortcomings in respect to digitalization can be identified in the Romanian healthcare system and these may impact public health. Digitalization may contribute fundamentally to the improvement of public health by increasing performance. However, in the context of the COVID-19 pandemic, other ailments that burden the healthcare system should not be neglected (cardiovascular diseases, malignancies, etc.).

Substance Abuse and Drug-Related Death, Suicidal Ideation, and Suicide: A Review

Crisis ◽  
1999 ◽  
Vol 20 (1) ◽  
pp. 28-35 ◽  
Author(s):  
Annie Mino ◽  
Arnaud Bousquet ◽  
Barbara Broers
Keyword(s):  
Public Health ◽  
Risk Factors ◽  
Substance Abuse ◽  
Suicidal Ideation ◽  
Family Support ◽  
Drug Users ◽  
Suicide Attempts ◽  
Public Health Problem ◽  
Major Public Health Problem ◽  
Hiv Epidemic

The high mortality rate among drug users, which is partly due to the HIV epidemic and partly due to drug-related accidental deaths and suicides, presents a major public health problem. Knowing more about prevalence, incidence, and risk factors is important for the development of rational preventive and therapeutic programs. This article attempts to give an overview of studies of the relations between substance abuse, suicidal ideation, suicide, and drug-related death. Research in this field is hampered by the absence of clear definitions, and results of studies are rarely comparable. There is, however, consensus about suicidal ideation being a risk factor for suicide attempts and suicide. Suicidal ideation is also a predictor of suicide, especially among drug users. It is correlated with an absence of family support, with the severity of the psychosocial dysfunctioning, and with multi-drug abuse, but also with requests for treatment. Every clinical examination of a drug user, not only of those who are depressed, should address the possible presence of suicidal ideation, as well as its intensity and duration.

Crucial role of physiotherapy in treating COVID-19 patients

2020 ◽  
Vol 11 (SPL1) ◽  
pp. 967-971
Author(s):  
Poonam Thakre ◽  
Waqar M. Naqvi ◽  
Trupti Deshmukh ◽  
Nikhil Ingole ◽  
Sourabh Deshmukh
Keyword(s):  
Public Health ◽  
Distress Syndrome ◽  
Public Health Problem ◽  
Public Health Emergency ◽  
High Rate ◽  
Major Public Health Problem ◽  
Front Line ◽  
The Many ◽  
Sixth International

The emergence in China of 2019 of severe acute respiratory syndrome coronavirus2 (SARS-CoV-2) previously provisionally names 2019-nCoV disease (COVID19) caused major global outbreak and is a major public health problem. On 30 January 2020, the WHO declared COVID19 to be the sixth international public health emergency. This present pandemic has engrossed the globe with a high rate of mortality. As a front line practitioner, physiotherapists are expected to be getting in direct contact with patients infected with the virus. That’s why it is necessary for understanding the many aspects of their role in the identification, contains, reduces and treats the symptoms of this disease. The main presentation is the involvement of respiratory system with symptoms like fever, cough, sore throat, sneezing and characteristics of pneumonia leads to ARDS(Acute respiratory distress syndrome) also land up in multiorgan dysfunction syndrome. This text describes and suggests physiotherapy management of acute COVID-19 patients. It also includes recommendations and guidelines for physiotherapy planning and management. It also covers the guidelines regarding personal care and equipment used for treatment which can be used in the treatment of acute adult patients with suspected or confirmed COVID-19.

scholarly journals Extensible artificial intelligence model predicts post-ablation AF recurrence using coronary sinus electrogram

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
D Huang ◽  
Z Zhang ◽  
K Lin ◽  
Z Zuo ◽  
Q Chen ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Catheter Ablation ◽  
Coronary Sinus ◽  
Public Health Problem ◽  
Adverse Outcomes ◽  
Funding Source ◽  
Major Public Health Problem ◽  
Deep Convolutional Neural Networks ◽  
F Measure ◽  
Af Recurrence

Abstract Background Atrial fibrillation (AF) is a major public health problem with significant adverse outcomes and catheter ablation is a widely adopted treatment. The CABANA trial showed that catheter ablation reduced AF recurrence to a greater extent than medications. However, some of patients who underwent this procedure still experience relapse. Here, we present an innovative way to identify this subgroup using an artificial intelligence (AI) -assisted coronary sinus electrogram. Hypothesis Our hypothesis is that credible features in the electrogram can be extracted by AI for prediction, therefore rigorous drug administration, close follow-up or potential second procedure can be applied to these patients. Methods 67 patients from two independent hospitals (SPH & ZSH) with non-valvular persistent AF undergoing circumferential pulmonary vein isolation were enrolled in this study, 23 of which experienced recurrence 6 months after the procedure. We collected standard 2.5-second fragments of coronary sinus electrogram from ENSITE NAVX (SPH) and Carto (ZSH)system before the ablation started. A total of 1429 fragments were obtained and a transfer learning-based ResNet model was employed in our study. Fragments from ZSH were used for training and SPH for validation of deep convolutional neural networks (DCNN). The AI model performance was evaluated by accuracy, recall, precision, F-Measure and AUC. Results The prediction accuracy of the DCNN in single center reached 96%, while that in different ablation systems reached 74.3%. Also, the algorithm yielded values for the AUC, recall, precision and F-Measure of 0.76, 86.1%, 95.9% and 0.78, respectively, which shows satisfactory classification results and extensibility in different cardiology centers and brands of electroanatomic mapping instruments. Conclusions Our work has revealed the potential intrinsic correlation between coronary sinus electrical activity and AF recurrence using DCNN-based model. Moreover, the DCNN model we developed shows great prospects in the relapse prediction for personalized post-procedural management. Funding Acknowledgement Type of funding source: Foundation. Main funding source(s): The National Natural Science Foundation of China

scholarly journals Leveraging Artificial Intelligence and Big Data to Optimize COVID-19 Clinical Public Health and Vaccination Roll-Out Strategies in Africa

2021 ◽  
Vol 18 (15) ◽  
pp. 7890
Author(s):  
Bruce Mellado ◽  
Jianhong Wu ◽  
Jude Dzevela Kong ◽  
Nicola Luigi Bragazzi ◽  
Ali Asgary ◽  
...  
Keyword(s):  
Public Health ◽  
Artificial Intelligence ◽  
Machine Learning ◽  
Big Data ◽  
Developed Countries ◽  
Machine Learning Techniques ◽  
Multiple Data ◽  
Learning Techniques ◽  
Unequal Access ◽  
Roll Out

COVID-19 is imposing massive health, social and economic costs. While many developed countries have started vaccinating, most African nations are waiting for vaccine stocks to be allocated and are using clinical public health (CPH) strategies to control the pandemic. The emergence of variants of concern (VOC), unequal access to the vaccine supply and locally specific logistical and vaccine delivery parameters, add complexity to national CPH strategies and amplify the urgent need for effective CPH policies. Big data and artificial intelligence machine learning techniques and collaborations can be instrumental in an accurate, timely, locally nuanced analysis of multiple data sources to inform CPH decision-making, vaccination strategies and their staged roll-out. The Africa-Canada Artificial Intelligence and Data Innovation Consortium (ACADIC) has been established to develop and employ machine learning techniques to design CPH strategies in Africa, which requires ongoing collaboration, testing and development to maximize the equity and effectiveness of COVID-19-related CPH interventions.

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