Covid-19 and Diabetes Risk Prediction for Diabetic Patient using Advance Machine Learning Techniques and Fuzzy Inference System

Diabetes has become a common and critical disease which generally occurs due to the presence of high sugar in blood for long time. A diabetic patient has to follow different rules and restrictions where he/she has to be under proper attention by measuring diabetes level frequently to avoid unexpected risk. The risk become more when patient even doesn't know that he/she is already having diabetes and doesn't follow those restrictions. To prevent this risk, everyone should check the diabetes status to be sure. With the same target different system using machine learning techniques have been introduced which can predict the diabetes status of a patient. But the challenging fact is that the performances and accuracy of those models are questionable where there may be a huge risk of patient's life. The conventional systems are not able to show that which level of diabetes a patient can have using the previous records. To solve this issue, through this paper an efficient system has been proposed with which the diabetes status can be predicted correctly. The proposed system can also show the complexity of diabetes as well as the Covid-19 risk percentage that can also be possible to measure. After comparing several machine learning techniques, the suitable model has been selected where high level of accuracy has been ensured in term of predicting the disease. © 2022 IEEE.

Dilated Cardiomyopathy: Unmasking Contributing Etiologies

Background: The role of genetic conditions in the development of cardiomyopathy is well established;however, recognition and referral for genetic testing remains underutilized. Systematic review of complex cases can increase general awareness in this area of practice. Here we describe the case of a patient with resolved severe stress induced cardiomyopathy (SIC), who was ultimately found to have heterozygous transthyretin-mediated amyloidosis (TTRA). Case: A 27-year-old man (family history positive for a brother status post heart transplant) presented with ataxia and cough due to legionella pneumonia. TTE showed left ventricular (LV) diastolic diameter of 6.2cm, LV ejection fraction 20-25%. He suffered rapid decompensation with mixed cardiogenic/septic shock requiring peripheral VA ECMO and Impella-CP placement. Course notable for brief cardiac arrest on hospital day (HD) 2, incidental diagnosis of COVID 19 on HD 14, conversion to VV ECMO on HD 15, and ECMO decannulation on HD 23. Repeat TTE prior to discharge showed normalization of biventricular function. Discussion(s): Despite resolution of refractory shock and normalization of biventricular function prior to discharge, the TTE finding of mild LV dilation and strong family history prompted outpatient pursuit of genetic testing which revealed a heterozygous TTRA mutation (val142ile). Work-up to assess cardiac involvement included: a 99m-technetium pyrophosphate scintigraphy found to be indeterminate, an aborted endomyocardial biopsy due to inability to smoothly advance a bioptome (presumably related to ECMO cannulation), and a cardiac MRI (pending at the time of this submission). If a cardiac phenotype is discovered, the patient will be started on targeted treatment of cardiac amyloid. Screening of first-degree family members has been initiated. Conclusion(s): Given the current state of under-diagnosis of genetic cardiomyopathies and its association with significant morbidity and mortality, it is prudent to consider genetic testing in young patients based on clinical history. Examples of clinical scenarios to prompt further testing include: anatomical findings (i.e. cardiac chamber enlargement, left ventricular hypertrophy), family history of cardiomyopathy, or clinical markers suggestive of alternative diagnoses (i.e. neuropathy, renal insufficiency, mediastinal lymphadenopathy). This thoughtful and algorithmic use of genetic testing may help improve long-term patient outcomes given improvements in both detection, family screening, and treatment for disease-specific cardiomyopathies.Copyright © 2022

COVID-19: An Insight on the Third Respiratory Global Emergency of the Century

Introduction: COVID-19 presents a global emergency in recent days and as a consequence, the whole world is in a state of war. Continuous efforts by researchers are being made to establish a sound scientific understanding regarding the behavior of the virus and its pathogenesis. Background(s): In recent days, a lot of scientific data are published describing viral transfusion into host cells, compared with SARS-CoV-1, viability of SARS-CoV-2, fatality and diagnosis of infection among infected patients, thereby, motivating to make right decisions in order to treat and mitigate COVID-19. Review Results: Coronaviruses usually affect the respiratory tract and produce symptoms similar to pneumonia with varied complications. The spike protein on the surface of the virus makes the SARS-CoV-2 phylogenetically different from other viruses of the corona family. SARS-CoV-2 has an affinity to angiotensin converting enzyme-2 receptors present on human cells. The fatality of the disease is found to be low, but the severity of the disease might vary from person to person. The incubation period is 14 days but the symptoms like dry cough and high fever are evident around 3-7 days. Already known anti-inflammatory immunomodulators and antiviral drugs are being tested and still under clinical trials. Conclusion(s): In this review, we are providing an insight into emergence of COVID-19, its correlation with SARS-CoV-1 and the interpretation of global data representing the severity of unexpected dangers for humanity. Certain structural aspects and studies determining the viability of novel coronavirus have also been described. Moreover, case studies of recovered infected patients from COVID-19 explain the progression and patients' pathophysiological conditions while suffering from the infection. Clinical Significance: There are many current strategies which are being tried and practiced to over-come this pandemic disease apart from precautionary measures. Although now, some decline has been seen, but the question still remains the same of whether the scientists are approaching towards the clinical solution, or are still in the midstream. This requires more study and intensive research to finally come to a concrete conclusion.Copyright © 2021 Bentham Science Publishers.

Formal Concept Analysis Applications in Bioinformatics

The bioinformatics discipline seeks to solve problems in biology with computational theories and methods. Formal concept analysis (FCA) is one such theoretical model, based on partial orders. FCA allows the user to examine the structural properties of data based on which subsets of the dataset depend on each other. This article surveys the current literature related to the use of FCA for bioinformatics. The survey begins with a discussion of FCA, its hierarchical advantages, several advanced models of FCA, and lattice management strategies. It then examines how FCA has been used in bioinformatics applications, followed by future prospects of FCA in those areas. The applications addressed include gene data analysis (with next-generation sequencing), biomarkers discovery, protein-protein interaction, disease analysis (including COVID-19, cancer, and others), drug design and development, healthcare informatics, biomedical ontologies, and phylogeny. Some of the most promising prospects of FCA are identifying influential nodes in a network representing protein-protein interactions, determining critical concepts to discover biomarkers, integrating machine learning and deep learning for cancer classification, and pattern matching for next-generation sequencing.

An Assessment of the Missing Data Imputation Techniques for COVID-19 Data

In medical domain, the accuracy of the data supplied is critical. Missing values, on the other hand, are a typical occurrence in this sector for a variety of reasons. Most current science concentrates on establishing novel data imputation procedures, but more research on conducting a comprehensive review of existing algorithms is highly desired. Authors have evaluated the performance of four mostly adopted data imputation techniques, i.e., MICE, EM, mean, and KNN on a real-world dataset of COVID-19. KNN is an imputation approach that, according to the findings of the studies, is expected to be a good fit for dealing with missing data in the healthcare industry. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Comparison of Different RNA Extraction Methods for Detection of SARS-Cov-2by RT-PCR

Background: Corona virus disease 2019 is a highly infectious disease which is caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2. SARS-CoV-2 is transmitted from person to person mainly by respiratory droplets and aerosols as well as by direct or indirect contact. Aims and objective: To compare different RNA extraction methods for detection of SARSCov-2 RNA from nasopharyngeal and oropharyngeal swabs using three different methods which are based on different techniques. Material and methods: This analytical observational study was conducted in the department of Microbiology, Sawai Man Singh Medical College Jaipur, Rajasthan from December 2020 to January 2021. We selected 200 confirmed positive (extracted by Easy Mag automated system) (remnant) samples showing a wide range of different Ct values and 20 confirmed negative samples stored in Viral Transport Media VTM for this study. In order to compare quality of three extractions methods, all samples were aliquoted separately for each extraction technique. (1) Extraction by manual method (spin column base): was done by as per manufacturer’s instructions. (2) Extraction by QIA cube HT (vaccum column base): was done by as per manufacturer’s instructions. (3) Extraction by Perkins Elmer chemagic 360: (magnetic beads based). Result: A panel consisting of 200 Covid-19 positive and 20 Covid-19 negative samples were extracted by three methods (i.e. Manual column based, automated column-based and automated magnetic beads-based method). The extracted material/elutes were put for realtime RT-PCR assay for the detection of SARS CoV-2 RNA. There was no major difference seen in individual samples’ ct values between three extraction system. CONCLUSION: In conclusion, we recommended all three RNA extraction methods (i.e. magnetic beads & silica column-based) are interchangeable in a diagnostic workflow for the SARS CoV-2 by RTPCR and can be taken into account for SARS CoV-2 detection in possible future shortage of one kit or times of crisis in such pandemic time.

Traditional vs e-teaching learning due to covid-19: A case study for mathematics course

As the trend towards E-teaching learning strengthens,questions remain unanswered with the effectiveness of online learning in comparison to traditional classroom learning. The aim of this paper is to analyze the impact of online and offline (conventional method) teaching method on student's learning achievement. This article outlines a case study of E-teaching vs traditional teaching learning of a Mathematics course to first year engineering students within their respective programmes. The results of study are analyzed using bar/pie charts. Comparison between online teaching and traditional teaching has been done for various parameters related to students’ interest for online/offline teaching, interaction with students, students' comfort level, instructor’s competency etc. related to teaching and learning. The findings generate insights which help to understand the benefits and shortcomings of online/offline teaching consequently helping in improved design of such courses. © 2021, Rajarambapu Institute Of Technology. All rights reserved.

COVID-19 pandemic: from origins to outcomes. A comprehensive review of viral pathogenesis, clinical manifestations, diagnostic evaluation, and management

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), the causative pathogen for the COVID-19, first emerged in Wuhan, China, in December 2019 and by March 2020, it was declared a pandemic. COVID-19 pandemic has overburdened healthcare systems in most countries and has led to massive economic losses. SARS-CoV-2 transmission typically occurs by respiratory droplets. The average incubation period is 6.4 days and presenting symptoms typically include fever, cough, dyspnea, myalgia or fatigue. While the majority of patients tend to have a mild illness, a minority of patients develop severe hypoxia requiring hospitalization and mechanical ventilation. Management is mostly supportive. However, several direct anti-viral agents, and immunomodulatory therapy with steroids and various cytokine blockers seem promising in early results. However, an effective vaccine has been established, which will help curb the pandemic.