Healthcare professionals routinely use audio signals, generated by the human body, to help diagnose disease or assess its progression. With new technologies, it is now possible to collect human-generated sounds, such as coughing. Audio-based machine learning technologies can be adopted for automatic analysis of collected data. Valuable and rich information can be obtained from the cough signal and extracting effective characteristics from a finite duration time interval that changes as a function of time. This article presents a proposed approach to the detection and diagnosis of COVID-19 through the processing of cough collected from patients suffering from the most common symptoms of this pandemic. The proposed method is based on adopt

Little is known about hesitancy to receive the COVID‐19 vaccines. The objectives of this study were (1) to assess the perceptions of healthcare workers (HCWs) and the general population regarding the COVID‐19 vaccines, (2) to evaluate factors influencing the acceptance of vaccination using the health belief model (HBM), and (3) to qualitatively explore the suggested intervention strategies to promote the vaccination.

Abstract

Background: The novel coronavirus 2 (SARS?CoV?2) pandemic is a pulmonary disease, which leads to cardiac, hematologic, and renal complications. Anticoagulants are used for COVID-19 infected patients because the infection increases the risk of thrombosis. The world health organization (WHO), recommend prophylaxis dose of anticoagulants: (Enoxaparin or unfractionated Heparin for hospitalized patients with COVID-19 disease. This has created an urgent need to identify effective medications for COVID-19 prevention and treatment. The value of COVID-19 treatments is affected by cost-effectiveness analysis (CEA) to inform relative value and how to best maximize social welfare through eviden

Abstract Background: The novel coronavirus 2 (SARS?CoV?2) pandemic is a pulmonary disease, which leads to cardiac, hematologic, and renal complications. Anticoagulants are used for COVID-19 infected patients because the infection increases the risk of thrombosis. The world health organization (WHO), recommend prophylaxis dose of anticoagulants: (Enoxaparin or unfractionated Heparin for hospitalized patients with COVID-19 disease. This has created an urgent need to identify effective medications for COVID-19 prevention and treatment. The value of COVID-19 treatments is affected by cost-effectiveness analysis (CEA) to inform relative value and how to best maximize social welfare through evidence-based pricing decisions. O

The increased use of hybrid PET /CT scanners combining detailed anatomical information along withfunctional data has benefits for both diagnostic and therapeutic purposes. This presented study is to makecomparison of cross sections to produce 18F , 82Sr and68Ge via different reactions with particle incident energy up to 60 MeV as a part of systematic studies on particle-induced activations on enriched natNe, natRb, natGa 18O,85Rb, and 69Ga targets, theoretical calculation of production yield, calculation of requiredtarget and suggestion of optimum reaction to produce: Fluorine-18 , Strontium-82 andGermanium-68 touse in Hybrid Machines PET/CT Scanners.

The simple and available technique of colorimetry and indirect X-ray fluorescence determination of tetracycline hydrochloride (in the form of colored complex with iron(III) ions) and cyanocobalamine (in the form of the colored thiocyanate complex with cobalt(II) ions) is offered. The analytes were separated from the accompanying components by sorption to polyurethane foam based on ethers. The conditions of sorption separation and measurement of analytical signal of these substances are optimized. The obtained results of tetracycline drugs and injection solution B₁₂ vitamin are in satisfactory agreement with data declared by the manufacturer.

The automatic estimation of speaker characteristics, such as height, age, and gender, has various applications in forensics, surveillance, customer service, and many human-robot interaction applications. These applications are often required to produce a response promptly. This work proposes a novel approach to speaker profiling by combining filter bank initializations, such as continuous wavelets and gammatone filter banks, with one-dimensional (1D) convolutional neural networks (CNN) and residual blocks. The proposed end-to-end model goes from the raw waveform to an estimated height, age, and gender of the speaker by learning speaker representation directly from the audio signal without relying on handcrafted and pre-computed acou

Beyond the immediate content of speech, the voice can provide rich information about a speaker's demographics, including age and gender. Estimating a speaker's age and gender offers a wide range of applications, spanning from voice forensic analysis to personalized advertising, healthcare monitoring, and human-computer interaction. However, pinpointing precise age remains intricate due to age ambiguity. Specifically, utterances from individuals at adjacent ages are frequently indistinguishable. Addressing this, we propose a novel, end-to-end approach that deploys Mozilla's Common Voice dataset to transform raw audio into high-quality feature representations using Wav2Vec2.0 embeddings. These are then channeled into our self-attentio

Coronavirus: (COVID-19) is a recently discovered viral disease caused by a new strain of coronavirus.

The majority of patients with corona-virus infections will have a mild-moderate respiratory disease that recovers without special care. Most often, the elderly, and others with chronic medical conditions such as asthma, coronary disease, respiratory illness, and malignancy are seriously ill.

    COVID-19 is spread mostly by salivary droplets or nasal secretions when an infected person coughs or sneezes.

    COVID-19 causes severe acute respiratory illness (SARS-COV-2). The first incidence was recorded in Wuhan, China, in 2019.  Since then it spreads leading to a pandemic.