scholarly journals Marie: Validation of the Artificial Intelligence Model for Covid-19 Detection

2021 ◽  
Vol 13 (4) ◽  
Author(s):  
Valdirene Bento ◽  
Bruno Frederico Salaroli ◽  
Paula Santos
Keyword(s):  
Artificial Intelligence ◽  
Computational Model ◽  
Computational Methods ◽  
Health Professionals ◽  
Recognition Accuracy ◽  
Signs And Symptoms ◽  
Minas Gerais ◽  
Streptococcus Pneumonia ◽  
X Ray

Lung X-ray images, if processed using statistical and computational methods, can distinguish pneumonia from COVID-19. The present work shows that it is possible to extract lung X-ray characteristics to improve the methods of examining and diagnosing patients with suspected COVID-19, distinguishing them from malaria, tuberculosis, and Streptococcus pneumonia. More precisely, an intelligent computational model was developed to process lung X-ray images and classify whether the image is of a patient with COVID-19. In partnership with the municipality of Itapeva, Minas Gerais, we carried out patient analysis and, at the same time, we evolved the algorithms to meet the needs of health professionals and also expand support in tracking COVID-19 in the municipality. In this project we will describe cases and even signs and symptoms that were similar to the clinical performed by the doctor. The average recognition accuracy of COVID-19 was 0.97,4 ± 0.043.

scholarly journals Intelligent Computational Model for the Classification of Covid-19 with Chest Radiography Compared to other Respiratory Diseases

2021 ◽  
Author(s):  
Paula Santos
Keyword(s):  
Computational Model ◽  
Bayesian Information Criterion ◽  
Respiratory Diseases ◽  
Recognition Accuracy ◽  
Information Criterion ◽  
Streptococcus Pneumonia ◽  
X Ray ◽  
Pulmonary Pathology ◽  
Statistical Learning Method

Lung X-ray images, if processed using statistical and computational methods, can distinguish pneumonia from COVID-19. The present work shows that it is possible to extract lung X-ray characteristics to improve the methods of examining and diagnosing patients with suspected COVID-19, distinguishing them from malaria, dengue, H1N1, tuberculosis, and Streptococcus pneumonia. More precisely, an intelligent computational model was developed to process lung X-ray images and classify whether the image is of a patient with COVID-19. The images were processed and extracted their characteristics. These characteristics were the input data for an unsupervised statistical learning method, PCA, and clustering, which identified specific attributes of X-ray images with Covid-19. The introduction of statistical models allowed a fast algorithm, which used the X-means clustering method associated with the Bayesian Information Criterion (CIB). The developed algorithm efficiently distinguished each pulmonary pathology from X-ray images. The method exhibited excellent sensitivity. The average recognition accuracy of COVID-19 was 0.93 ± 0.051.

scholarly journals Community-acquired pneumonia in patients admitted to National District Hospital in Bloemfontein: guideline adherence

2018 ◽  
Vol 60 (6) ◽  
pp. 43
Author(s):  
Thornton Ford ◽  
Johané Potgieter ◽  
Jana Van der Walt ◽  
Monette Van Schalkwyk ◽  
Maresa Van Lill ◽  
...  
Keyword(s):  
Guideline Adherence ◽  
Health Professionals ◽  
Treatment Guidelines ◽  
District Hospital ◽  
Treatment Guideline ◽  
Signs And Symptoms ◽  
Community Acquired Pneumonia ◽  
X Ray ◽  
Study Population ◽  
Chest X Ray

Background: Patients with suspected community-acquired pneumonia (CAP) are managed according to treatment guidelines. This study aimed to determine the guideline adherence of health professionals at National District Hospital (NDH), Bloemfontein.Methods: This retrospective descriptive study included a study population of 149 patients admitted to NDH with suspected CAP from January 2015 to September 2016. Information was noted from the patient files and included signs and symptoms, investigations done and medication prescribed.Results: Most patients (n = 111, 75.0%) presented with a cough, 87 (60.0%) had a sputum test and 125 (83.9%) had a chest X-ray of whom 108 (86.4%) had a consolidation on the X-ray. The CURB-65 score of five (3.4%) patients was mentioned in the files, of which only three patients’ scores were indicated. One patient had a noted CURB-65 score that required admission.Conclusion: The adherence of health professionals to the treatment guideline for suspected CAP patients is poor.

scholarly journals Training Artificial Intelligence Neural Networks to Detect Devices on a Chest X-ray, a Pathway to COVID-19 Testing

2020 ◽  
Vol 112 (5) ◽  
pp. S50
Author(s):  
Zachary Eller ◽  
Michelle Chen ◽  
Jermaine Heath ◽  
Uzma Hussain ◽  
Thomas Obisean ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Neural Networks ◽  
X Ray ◽  
Chest X Ray

scholarly journals Deep learning for visualization and novelty detection in large X-ray diffraction datasets

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Lars Banko ◽  
Phillip M. Maffettone ◽  
Dennis Naujoks ◽  
Daniel Olds ◽  
Alfred Ludwig
Keyword(s):  
Thin Film ◽  
Crystal Structure ◽  
Artificial Intelligence ◽  
Deep Learning ◽  
Novelty Detection ◽  
Structural Similarity ◽  
X Ray Diffraction ◽  
X Ray ◽  
Diffraction Patterns ◽  
Post Hoc

AbstractWe apply variational autoencoders (VAE) to X-ray diffraction (XRD) data analysis on both simulated and experimental thin-film data. We show that crystal structure representations learned by a VAE reveal latent information, such as the structural similarity of textured diffraction patterns. While other artificial intelligence (AI) agents are effective at classifying XRD data into known phases, a similarly conditioned VAE is uniquely effective at knowing what it doesn’t know: it can rapidly identify data outside the distribution it was trained on, such as novel phases and mixtures. These capabilities demonstrate that a VAE is a valuable AI agent for aiding materials discovery and understanding XRD measurements both ‘on-the-fly’ and during post hoc analysis.

scholarly journals Current limitations to identify COVID-19 using artificial intelligence with chest X-ray imaging

2021 ◽  
Vol 11 (2) ◽  
pp. 411-424 ◽  
Author(s):  
José Daniel López-Cabrera ◽  
Rubén Orozco-Morales ◽  
Jorge Armando Portal-Diaz ◽  
Orlando Lovelle-Enríquez ◽  
Marlén Pérez-Díaz
Keyword(s):  
Artificial Intelligence ◽  
X Ray ◽  
X Ray Imaging ◽  
Chest X Ray

Artificial intelligence X-ray measurement technology of anatomical parameters related to lumbosacral stability

2021 ◽  
pp. 110071
Author(s):  
Sheng Zhou ◽  
Hongyan Yao ◽  
Chunyu Ma ◽  
Xiaofei Chen ◽  
Wenqi Wang ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Measurement Technology ◽  
X Ray ◽  
Anatomical Parameters

Cyclometalated Pt(ii) complexes with a bidentate Schiff-base ligand displaying unexpected cis/trans isomerism: synthesis, structures and electronic properties

2017 ◽  
Vol 46 (37) ◽  
pp. 12500-12506 ◽  
Author(s):  
A. Poma ◽  
A. Forni ◽  
C. Baldoli ◽  
P. R. Mussini ◽  
A. Bossi
Keyword(s):  
Schiff Base ◽  
Electronic Properties ◽  
Computational Methods ◽  
Schiff Base Ligand ◽  
X Ray Diffraction ◽  
X Ray ◽  
Bidentate Schiff Base Ligand

Unexpected cis/trans isomerism in a bis-cyclometalated Pt(ii) complex is investigated by NMR, X-ray diffraction, optical, electrochemical and computational methods and rationalized.

scholarly journals Foreign Body Aspiration in Infants and Older Children: A Comparative Study

2019 ◽  
Vol 99 (1) ◽  
pp. 47-51 ◽  
Author(s):  
Shorook Na’ara ◽  
Igor Vainer ◽  
Moran Amit ◽  
Arie Gordin
Keyword(s):  
Foreign Body ◽  
Medical Center ◽  
Age Groups ◽  
Signs And Symptoms ◽  
Foreign Body Aspiration ◽  
Preschool Age ◽  
Small Airways ◽  
Older Children ◽  
X Ray ◽  
Young Infants

Background: Foreign body aspiration (FBA) is a major cause of morbidity and mortality in children. It is a preventable event that predominates in preschool age. The signs and symptoms mimic respiratory diseases common in the same age-group. We compared FBA in infants to FBA in older children. Methods: Retrospective analysis of all the cases of suspected FBA of children under the age of 18 years hospitalized at one medical center during 2002 to 2016. We analyzed the data according to age: up to 1 year (infants) and 1 to 18 years. Results: One hundred seventy-five children with suspected FBA were admitted; of whom, 27 (15%) were infants and 148 (85%) were older children (age 1-18 years). For the 2 age groups, adults witnessed 85% and 73%, respectively, of the incidents ( P = .4). In the neonate group, 48% presented with normal X-ray findings compared to only 20% in the older group; 15% of the older group had a positive chest X-ray for a foreign body, while none had such in the infants’ group ( P = .01). For the 2 age groups, the majority of the FBs found were from organic origin. About half of the patients were diagnosed and managed within 24 hours of the aspiration event. In 10%, repeated bronchoscopy was performed due to a retained FB remnant. In a multivariate analysis, signs and symptoms ( P < .05), location of the FB ( P < .001), and witnessed aspiration ( P < .001) were independent prognostic factors for the length of hospitalization. Conclusion: Foreign body aspiration is not uncommon in young infants; the management is challenging due to small airways, the need to use smaller bronchoscopes, and the lack of working channel forces in pediatric bronchoscopes.

scholarly journals A case of tooth fracture occurred upon medicating bisphosphonate for an elderly person: Preservation therapy and responses for Stage 0 of bisphosphonate-related osteonecrosis of jaw

2017 ◽  
Vol 11 (02) ◽  
pp. 258-263
Author(s):  
Noriko Suzuki ◽  
Hitoshi Oguchi ◽  
Yu Yamauchi ◽  
Yasuyo Karube ◽  
Yukimi Suzuki ◽  
...  
Keyword(s):  
Elderly Person ◽  
Signs And Symptoms ◽  
Apical Position ◽  
X Ray ◽  
Second Molar ◽  
Tooth Fracture ◽  
Molar Teeth ◽  
Osteonecrosis Of Jaw ◽  
Bone Exposure ◽  
Symptoms And Signs

ABSTRACTThis case report aimed to report the progress of preservation therapy and response of symptoms and signs for Stage 0 of bisphosphonate-related osteonecrosis of jaw (BRONJ). A 68-year-old female was recognized having a tooth at the left upper first molar fracture upon medicating bisphosphonate (BP) in 2007. At that time, the extraction of the tooth was an absolute contraindication. Therefore, we performed preservation therapy. We observed the symptoms and signs every month. After 5 months, swelling and redness in the entire first molar tooth were seen and fistula formed partly. Bone exposure was not seen. We administrated antibiotics immediately. As a result, symptoms disappeared. On April 10, 2009, the patient visited us as she felt a sense of incongruity in the lower left first and second molar teeth. Clinically, there were no symptoms of pain. However, we observed the radiolucent finding in about 5 mm diameter at apical position by X-ray photography; we considered a possibility of Stage 0 for BRONJ. We immediately administered medicine for 5 days and the symptoms disappeared. At present, no inflammation with signs and symptoms at the upper left first molar and lower left first, second molar parts is shown. We performed preservation therapy for tooth fracture case medicating of BP. Immediate responses for inflammation and symptoms of the Stage 0 of BRONJ have led to success. Hence, dentists should perform regular clinical observation, and enough education to the patient for BRONJ is necessary.

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