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Auto Summaries - Diagnostics
Last updated: 2022 Jan 4
Total hit(s): 9505
S.No.
1
34895104
Age and clinical signs as predictors of COVID-19 symptoms and cycle threshold value
Many COVID-19 infected people remain asymptomatic, and hence diagnosis at first presentation remains a challenge. Assessment at a presentation in primary care settings is usually done by visual triaging and basic clinical examination. This retrospective study involved investigating the medical e-records of patients who presented to a centre in Qatar for July 2020.
Libyan J Med
2022 Dec
1
2
34931582
Symptoms at disease onset predict prognosis in COVID-19 disease
The main clinical manifestations of coronavirus disease 2019 (COVID-19) onset are respiratory symptoms, including cough, sputum, and dyspnea. However, a significant proportion of patients initially manifested non-respiratory symptoms, such as fever, myalgia, and diarrhea. Respiratory patients had more secondary bacterial infections, needed the intensive care unit more (9.7% vs 2.2%, P =0.005), developed ARDS more (11.4%) and needed longer time to recover (18.5 vs 16.7 days)
Libyan J Med
2022 Dec
1
3
34907114
Prevalence of a Single-Nucleotide Variant of SARS-CoV-2 in Korea and Its Impact on the Diagnostic Sensitivity of the Xpert Xpress SARS-CoV-2 Assay
N/A
Ann Lab Med
2022 May 1
2.81
1
4
34907107
Incidence Evaluation of SARS-CoV-2 Variants in the Ulsan Area, Korea, Using PowerChek SARS-CoV-2 S-gene Mutation Detection Kit: A Pilot Study
Department of Laboratory Medicine, University of Ulsan College of Medicine, is a Korean hospital. It was founded in the 1950s and has been used as a research institution for more than 30 years. The lab results have been published on numerous occasions by South Korea's leading scientists.
Ann Lab Med
2022 May 1
2.81
1
5
34677155
Acute asthma exacerbation after SARS-CoV-2 vaccine (SinovacĀ®): a case report
A 76-year-old female received a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine (CoronaVac, Sinovac() and subsequently experienced chest discomfort. She was hospitalized with a preliminary diagnosis of drug-induced pneumonitis and acute asthma exacerbation. During her hospitalization, 40 mg/d systemic steroid, 4 times a day salbutamol nebulized, 2 L/min inhaled oxygen therapy and 400mg/d moxifloxacin intravenous were administered for 5 days. One month later, the thorax computed tomography scan revealed that the previous findings were almost completely regressed.
Med Gas Res
2022 Apr-Jun
1
6
34677154
Prediction of diagnosis and prognosis of COVID-19 disease by blood gas parameters using decision trees machine learning model: a retrospective observational study
Machine learning models can accurately assess hidden patterns among risk factors by analyzing large-datasets to quickly predict diagnosis, prognosis and mortality of diseases. This study was carried out on a total of 686 patients with COVID-19 (n = 343) and non-COVI-19 treated at Erzincan-Mengcek-Gazi-Training and Research-Hospital between April 1, 2020 and March 1, 2021. The findings in the study may aid in the early-diagnosis of the disease and the intensive-care treatment of patients who are severe.
Med Gas Res
2022 Apr-Jun
1
7
34677153
Ozone gas applied through nebulization as adjuvant treatment for lung respiratory diseases due to COVID-19 infections: a prospective randomized trial
The objective of this study was to provide lung disinfection by nebulizing ozone gas with distilled water and olive oil for patients who have clinical symptoms due to coronavirus disease 2019 (COVID-19) 30 patients who met the study criteria were prospectively evaluated. A statistically significant difference was found in the length of stay in hospital, change in C-reactive protein, polymerase chain reaction results after 5 days, and computed tomography scores between two groups.
Med Gas Res
2022 Apr-Jun
1
8
34937995
A novel unsupervised approach based on the hidden features of Deep Denoising Autoencoders for COVID-19 disease detection
The method proposed in this paper is based on the exploitation of the compact and meaningful hidden representation provided by a Deep Denoising Convolutional Autoencoder (DDCAE) The proposed DDCAE, trained on some target CT scans in an unsupervised way, is used to build up a robust statistical representation. A suitable statistical distance measures how this target histogram is far from a companion histogram evaluated on an unknown test scan. If this distance is greater of a threshold, the test image is labeled as anomaly, i.e. the scan belongs to a patient affected by COVID-19 disease.
Expert Syst Appl
2022 Apr 15
5.89
1
9
34924632
COVID-MTL: Multitask learning with Shift3D and random-weighted loss for COVID-19 diagnosis and severity assessment
Radiology and nucleic acid test (NAT) are complementary COVID-19 diagnosis methods. CoVID-MTL learns different tasks in parallel through a novel random-weighted loss function, which assigns learning weights under Dirichlet distribution to prevent task dominance. The framework is able to accelerate convergence and improve joint learning performance compared to single-task models.
Pattern Recognit
2022 Apr
7.35
1
10
34690450
A biological sub-sequences detection using integrated BA-PSO based on infection propagation mechanism: Case study COVID-19
The longest common consecutive subsequences (LCCS) play a vital role in revealing the biological relationships between DNA/RNA sequences especially the newly discovered ones such as COVID-19. FLAT is a Fragmented local aligner technique which is an accelerated version of the local pairwise sequence alignment algorithm based on meta-heuristic algorithms. This paper introduces a modified version of FLAT based on improving the performance of the BA algorithm by integration with particle swarm optimization (PSO) algorithm. It has a preponderance to find the LCCS with the highest percentage (88%) which is better than other state-of-the-art methods.
Expert Syst Appl
2022 Mar 1
5.89
2
11
34744186
Big data directed acyclic graph model for real-time COVID-19 twitter stream detection
" The aim of this work is to detect anomalous events associated with COVID-19 from Twitter. We obtained the three most commonly listed terms on Twitter: ""covid"", ""death"", and ""Trump"" (21,566, 11,779, and 4761 occurrences) On 18 August 2020, our model detected the highest anomaly since many tweets mentioned the casualties' updates and debates on the pandemic that day. These terms were located near each other on vector space so that they were clustered, indicating people's most concerned topics on Twitter."
Pattern Recognit
2022 Mar
7.35
1
12
34866796
COVID-19 diagnosis by SARS-CoV-2 Spike protein detection in saliva using an ultrasensitive magneto-assay based on disposable electrochemical sensor
The main technique used for diagnosing the Coronavirus disease (COVID-19) is the reverse transcription-polymerase chain reaction (RT-PCR) Technique. New magneto-assay uses magnetic beads and gold nanoparticles conjugated to human angiotensin-converting enzyme 2 (ACE2) peptide, Gln(24)-Gln(42) In terms of efficiency, the proposed technique presented a sensitivity of 100.0% and specificity of 93.7% for SARS-CoV-2 Spike protein.
Sens Actuators B Chem
2022 Feb 15
1
13
34690533
Electrochemical sensors for the detection of SARS-CoV-2 virus
The presently used methods include rapid antigen tests, serological surveys, reverse transcription-polymerase chain reaction (RT-PCR), artificial intelligence-based techniques, and assays based on sensors/biosensors. Recently, electrochemical sensors have been developed for rapid monitoring and detection of SARS-CoV-2 from the patient's biological fluid samples.
Chem Eng J
2022 Feb 15
N/A
2
14
34866797
Molecularly imprinted polymer based electrochemical sensor for quantitative detection of SARS-CoV-2 spike protein
An electrochemical sensor based on a molecularly imprinted polymer synthetic receptor for the quantitative detection of SARS-CoV-2 spike protein subunit S1. The sensor displays a satisfactory performance with a reaction time of 15min and is capable of detecting ncovS1 both in phosphate buffered saline and patient's nasopharyngeal samples with LOD values of 15 fM and 64 fM.
Sens Actuators B Chem
2022 Feb 15
1
15
34864792
Chest imaging in patients with acute respiratory failure because of coronavirus disease 2019
CT is the technique with higher sensitivity and definition for studying chest in COVID-19 patients. LUS or bedside CXR are critical in patients requiring close and repeated monitoring. PET/CT and MRI, especially in ARDS patients, are not usually used for diagnostic or follow-up purposes.
Curr Opin Crit Care
2022 Feb 1
2.51
1
16
34932525
Ventilator-associated pneumonia among SARS-CoV-2 acute respiratory distress syndrome patients
16 studies reviewed ventilator-associated pneumonia (VAP) in patients undergoing mechanical ventilation because of acute respiratory distress syndrome secondary to SARS-CoV-2 infection. Most episodes of VAP were associated with Gram-negative bacteria. Potential factors driving high VAP incidence rates include immunoparalysis, prolonged ventilation, exposure to immunosuppressants, understaffing, lapses in prevention processes, and overdiagnosis.
Curr Opin Crit Care
2022 Feb 1
2.51
1
17
34539223
Visual naked-eye detection of SARS-CoV-2 RNA based on covalent organic framework capsules
The ongoing outbreak of coronavirus disease 2019 (COVID-19) has highlighted that new diagnosis technologies are crucial for controlling the spread of the disease. We have designed a novel strategy to fabricate covalent organic framework (COF) capsules, which can be utilized to establish a new colorimetric assay for naked-eye detection of SARS-CoV-2 RNA.
Chem Eng J
2022 Feb 1
N/A
2
18
34866656
Fluorescence immunoassay rapid detection of 2019-nCoV antibody based on the fluorescence resonance energy transfer between graphene quantum dots and Ag@Au nanoparticle
A fluorescence immunoassay was developed to detect 2019 Novel Coronavirus antibodies (2019-nCoV mAb) GQDs and Ag@Au nanoparticles were successfully synthesized and characterized. The fluorescence enhancement efficiency has a satisfactory linear relationship with the logarithm of the 2019-ncovirus mAb in a concentration range of 0.1pgmL(-1), and the limit of detection was 50fgmL (-1)
Microchem J
2022 Feb
1
19
34903957
Towards an efficient collection and transport of COVID-19 diagnostic specimens using genetic-based algorithms
The Tunisian ministry of health established a protocol planning the sample collection from the patients at their location. A triage score is first assigned to each patient according to the symptoms he is showing, and his health conditions. Then, given the limited number of the available ambulances in each area, the location of the patients and the capacity of the nearby hospitals for receiving the samples, an ambulance scheduling and routing plan needs to be established so that specimens can be transferred to hospitals in short time.
Appl Soft Comput
2022 Feb
6.03
1
20
34688919
Yeast-expressed recombinant SARS-CoV-2 receptor binding domain RBD203-N1 as a COVID-19 protein vaccine candidate
SARS-CoV-2 protein subunit vaccines are currently being evaluated by multiple manufacturers to address the global vaccine equity gap, and need for low-cost, easy to scale, safe, and effective COVID-19 vaccines. In this paper, we report on the generation of the RBD203-N1 yeast expression construct, which produces a recombinant protein capable of eliciting a robust immune response and protection in mice against infections.
Protein Expr Purif
2022 Feb
1
21
34745319
ENResNet: A novel residual neural network for chest X-ray enhancement based COVID-19 detection
It is very difficult to detect the virus infected chest X-ray (CXR) image during early stages due to constant gene mutation of the virus. The suggested ENResNet achieves a classification accuracy 99.7% and 98.4% for binary classification and multi-class detection respectively in comparison with state-of-the-art methods.
Biomed Signal Process Control
2022 Feb
3.83
1
22
34931117
A novel ensemble fuzzy classification model in SARS-CoV-2 B-cell epitope identification for development of protein-based vaccine
B-cell epitope identification with the aid of an accurate prediction method is one of the most important steps in epitope-based vaccine development, immunodiagnostic testing, antibody production, disease diagnosis, and treatment. We hope that the developed epitope prediction method will help design effective vaccines and drugs against future outbreaks of the coronavirus family, especially SARS-CoV-2 and its possible mutations.
Appl Soft Comput
2022 Feb
6.03
1
23
34927119
Monitoring populations at increased risk for SARS-CoV-2 infection in the community using population-level demographic and behavioural surveillance
Real-time population screening and identification of groups in whom positivity is highest could help monitor spread and inform public health messaging and strategy. Of 4,091,537 RT-PCR results from 482,677 individuals, 29,903 (073%) were positive. As positivity rose September-November 2020, rates were independently higher in Northern England, major urban conurbations, more deprived areas, and larger households. Rates were also higher in those returning from abroad, and working in healthcare or outside of home.
Lancet Reg Health Eur
2022 Feb
n/a
1
24
34927163
Acute Pancreatitis in COVID-19-associated Multisystem Inflammatory Syndrome of Children-A Single Center Experience
A multisystem inflammatory syndrome in children (MIS-C) was identified as an entity temporally associated with the present COVID-19 pandemic. This inflammatory syndrome affects various organ systems including the gastrointestinal and hepatobiliary systems. Pancreatitis may be considered to be one of the parameters in the diagnostic criteria of MIS-C.
JPGN Rep
2022 Feb
1
25
34924896
One Shot Model For The Prediction of COVID-19 And Lesions Segmentation In Chest CT Scans Through The Affinity Among Lesion Mask Features
We present a novel framework that integrates segmentation of lesion masks and prediction of COVID-19 in chest CT scans in one shot. In order to classify the whole input image, we introduce a type of associations among lesion mask features extracted from the scan slice that we refer to as affinities. First, we map mask features to the affinity space by training an affinity matrix. Then we map them back into the feature space through a trainable affinity vector. This feature representation is used for the classification of the entire input scan slice. All source code, models and results are publicly available on https://github.com/AlexTS1980/COVID-Affinity-Model.
Appl Soft Comput
2022 Feb
6.03
1