Background: Coronavirus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-COV-2). Ground glass opacity, fibrous stripe, and thickening of adjacent pleura are frequently reported sequelae of COVID-19. COVID-19 causing severe bronchiectasis in a previously healthy individual with no underlying lung conditions, has not been reported in literature yet. Therefore, this case report aimed to highlight the importance of COVID-19 infection-causing unusual lung changes such as bronchiectasis. Case report: This case, a 44-year-old woman, came to the UNS hospital complaining of shortness of breath, fever, and cough. The patient had no previous history of lung disease. The results of chest Xray when he entered the ER showed bilateral pneumonia. After further examinations, the COVID-19 nasopharyngeal RT-PCR swab was confirmed and was obtained with comorbid chronic heart failure. During the treatment, the sputum culture was examined, and Pseudomonas aeruginosa was found. Two weeks after being declared cured of COVID-19, a chest X-ray and chest CT scan were performed, and bronchiectasis was obtained. Discussion: The long-term sequelae of COVID-19 infection is still being studied. Bronchiectasis is one of the scars of COVID-19 infection which can appear rapidly during COVID-19 infection. The predisposition for a sequela to COVID-19 in the form of bronchiectasis still requires further research, possibly due to the severe manifestations of COVID-19 infection. Comorbid and the development of bacterial pneumonia as the secondary infection was still suspected as predisposing factors for bronchiectasis in this case. Conclusion: Bronchiectasis is an atypical sequela of COVID-19, which gives a poor prognosis in post-COVID-19 patients because it reduces the patient's quality of life.
<p class="AbstractText">Telah berhasil dilakukan klasifikasi kanker paru-paru dari 120 data citra CT Scan. Pada penelitian, proses preposisi dimulai dengan variasi filtering yaitu low pass filter, median filter, dan high pass filter. Segmentasi yang digunakan yaitu Otsu Thresholding yang kemudian teksturnya akan diekstraksi menggunakan fitur Gray Level Co-occurrence Matrix (GLCM) dengan variasi arah sudut. Hasil dari ekstraksi GLCM dijadikan database yang akan menjadi dataset untuk pengklasifikasian citra menggunakan klasifikasi naïve bayes. Hasil dari penelitian dengan 12 buah variasi diperoleh hasil variasi terbaik adalah median filter dengan arah sudut GLCM 0° menunjukkan tingkat akurasi yang paling tinggi sebesar 88,33 %.</p>
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