Potential Method For Diagnosis Research Articles

Intelligent Internet of Things and Advanced Machine Learning Techniques for COVID-19

INTRODUCTION: Coronavirus disease (COVID-19) has recently emerged around the world. The beginning of the disease was in the Chinese city of Wuhan and then it has been spread and became a global epidemic. An early diagnosis of COVID-19 disease is absolutely necessary to control the epidemic.OBJECTIVES: The aim of this paper is to present a review of the contribution of machine learning (ML) and IoT to confront the epidemic.METHODS: Diagnosis using real-time reverse transcriptase-polymerase chain reaction (RT-PCR) is a definite diagnosis, but this method takes time, while a diagnosis using a computed tomography (CT) scan is a faster approach to diagnosis. However, a large number of patients need a CT scan, which puts a lot of pressure on the radiologist so visual fatigue may lead to diagnostic errors so there is an urgent need for additional solutions. Artificial intelligence (AI) is an efficient tool to combat COVID-19 disease. Computer scientists have been developing many systems to handle this epidemic.RESULTS: It was found that ML is an efficient and powerful AI technology that can be used for trustworthy COVID-19 detecting and diagnosis from X-ray and CT images and it can be a potential method for diagnosis in the radiology department. In addition, ML can be used in segmentation, prediction purposes for COVID-19. Furthermore, ML can effectively support drug discovery procedure and can reduce clinical failures.CONCLUSION: IoT has a significant role in monitoring an individual's health and COVID-19 diagnosis. This paper also highlights the challenges of employing ML and intelligent IoT for fighting COVID-19.

Cardiovascular risk and bipolar disorder: factors associated with a positive coronary calcium score in patients with bipolar disorder type 1.

Objective:Cardiovascular disease is the leading cause of death in patients with bipolar disorder. The aim of this study was to evaluate the factors associated with positive coronary calcium score (CCS) in individuals with bipolar disorder type 1.Methods:Patients from the Bipolar Disorder Program at Hospital de Clínicas de Porto Alegre, Brazil, underwent computed tomography scanning for calcium score measurement. Clinical and sociodemographic variables were compared between patients according to their CCS status: negative (CCS = 0) or positive (CCS > 0). Poisson regression analysis was used to examine the association of CCS with number of psychiatric hospitalizations.Results:Out of 41 patients evaluated, only 10 had a positive CCS. Individuals in the CCS-positive group were older (55.2±4.2 vs. 43.1±10.0 years; p = 0.001) and had more psychiatric hospitalizations (4.7±3.0 vs. 2.6±2.5; p = 0.04) when compared with CCS- negative subjects. The number of previous psychiatric hospitalizations correlated positively with CCS (p < 0.001).Conclusion:Age and number of psychiatric hospitalizations were significantly associated with higher CCS, which might be a potential method for diagnosis and stratification of cardiovascular disease in bipolar patients. There is a need for increased awareness of risk assessment in this population.

A potential method for identifying dural ossification by measuring the degree of spinal stenosis in thoracic ossification of ligamentum flavum

Ossification of ligamentum flavum (OLF) is increasingly recognized as the major cause of thoracic spinal stenosis. The dura mater beneath ossified ligamentum flavum may also ossify when the spinal stenosis develops to a certain degree. Preoperative diagnosis of dural ossification (DO) is beneficial for surgical management of OLF. However, currently, accurate diagnosis method still could not be obtained. Based on the association between spinal stenosis and OLF/DO, a potential diagnosis method is proposed in this paper: identifying DO by measuring the degree of spinal stenosis in thoracic OLF. In the early stage of OLF, there is only mild spinal stenosis and no DO. With the progression of OLF, dura may also ossify and further compress the spinal cord, aggravating spinal stenosis. Before DO, the dura mater is presented as a low signal intensity. Once ossifying, the dura mater will be shown as a high signal intensity in CT. It will lead that the degree of spinal stenosis measured in axial CT scan obviously increases. Thus, it provides a possibility to find a critical value of it for distinguishing OLF patients with or without DO.