| 2 | Clinical profile,etiology,management and outcome of empyema thoracis associated with COVID-19 infection:A systematic review of published case reports显示文摘Objective:To explore the clinical features,diagnosis,etiology,treatment,and outcomes of COVID-19 related empyema.Methods:Using PRISMA statement,a systematic search of relevant case reports published between December 2019 and April 2023 was performed through seven databases.The collected data included demographics,clinical manifestations,diagnostic findings,treatment,and outcomes.Results:Thirty-six case reports were identified with 43 cases of empyema.The included cases had a median age of 55 years(range:12-78 years)and 79.1%(34/43)were males.The majority of cases presented during hospitalization for management of acute COVID-19 infection(29/43,67.4%)and Charlson comorbidity index<3(40/43,93.0%).Pseudomonas aeruginosa was the most commonly isolated microorganism from the pleural fluid(9/43,20.9%)and 16.3%of the cases(7/43)had polymicrobial infections.Chest drainage was performed in all cases while surgery was indicated in 24 cases(55.8%).The most common complication of COVID-19-related empyema was broncho-pleural fistula(2/43,4.7%).The mortality rate was 23.3%(10/43).Sepsis and/or multi-organ failure were the most commonly reported causes of death.On univariate analysis,no statistically significant risk factor for mortality was identified.Conclusions:COVID-19-associated empyema has a variety of predisposing factors,time of presentation,clinical features,and causative organisms.Invasive or minimally invasive surgical procedures are performed more frequently than isolated chest drainage.Empyema in COVID-19 patients worsens their prognosis and can lead to serious complications. | Yasser Ali Kamal Seham Abdelwakeel Abdel-Gaber | 2023 | Asian Pacific Journal of Tropical Medicine2023，16，8： | 0 |
| 3 | Automated Speech Recognition System to Detect Babies’ Feelings through Feature Analysis显示文摘Diagnosing a baby’s feelings poses a challenge for both doctors and parents because babies cannot explain their feelings through expression or speech.Understanding the emotions of babies and their associated expressions during different sensations such as hunger,pain,etc.,is a complicated task.In infancy,all communication and feelings are propagated through cryspeech,which is a natural phenomenon.Several clinical methods can be used to diagnose a baby’s diseases,but nonclinical methods of diagnosing a baby’s feelings are lacking.As such,in this study,we aimed to identify babies’feelings and emotions through their cry using a nonclinical method.Changes in the cry sound can be identified using our method and used to assess the baby’s feelings.We considered the frequency of the cries from the energy of the sound.The feelings represented by the infant’s cry are judged to represent certain sensations expressed by the child using the optimal frequency of the recognition of a real-world audio sound.We used machine learning and artificial intelligence to distinguish cry tones in real time through feature analysis.The experimental group consisted of 50%each male and female babies,and we determined the relevancy of the results against different parameters.This application produced real-time results after recognizing a child’s cry sounds.The novelty of our work is that we,for the first time,successfully derived the feelings of young children through the cry-speech of the child,showing promise for end-user applications. | Sana Yasin Umar Draz Tariq Ali Kashaf Shahid Amna Abid Rukhsana Bibi Muhammad Irfan Mohammed A.Huneif Sultan A.Almedhesh Seham M.Alqahtani Alqahtani Abdulwahab Mohammed Jamaan Alzahrani Dhafer Batti Alshehri Alshehri Ali Abdullah Saifur Rahman | 2022 | Computers, Materials & Continua2022，，11： | 0 |
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