Deep features to detect pulmonary abnormalities in chest X-rays due to infectious diseaseX: Covid-19, pneumonia, and tuberculosis.

Mahbub, Md Kawsher; Biswas, Milon; Gaur, Loveleen; Alenezi, Fayadh; Santosh, K C

Mahbub, Md Kawsher; Biswas, Milon; Gaur, Loveleen; Alenezi, Fayadh; Santosh, K C.

Afiliação

Mahbub MK; Bangladesh University of Business and Technology, Rupnagar, Mirpur-2, Dhaka 1216, Bangladesh.
Biswas M; Bangladesh University of Business and Technology, Rupnagar, Mirpur-2, Dhaka 1216, Bangladesh.
Gaur L; Amity University, Gautam Buddha Nagar, 201313 Uttar Pradesh, India.
Alenezi F; Department of Electrical Engineering, College of Engineering, Jouf University, 72238, Saudi Arabia.
Santosh KC; 2AI: Applied Artificial Intelligence Research Lab - Computer Science, University of South Dakota, 414 E Clark St, Vermillion, SD 57069, USA.

Inf Sci (N Y) ; 592: 389-401, 2022 May.

Article em En | MEDLINE | ID: mdl-36532848

Palavras-chave

ACC, Accuracy; AI, Artificial Intelligence; AUC, Area Under the Curve; CADx, Computer-Aided Diagnosis; CNN, Convolutional Neural Network; CT, Computed Tomography; CXR, Chest X-ray; Chest X-ray; Covid-19; DL, Deep Learning; DNN; DNN, Deep Neural Network; Infectious DiseaseX; ML, Machine Learning; MTB, Mycobacterium Tuberculosis; Medical imaging; NN, Neural Network; Pneumonia; SEN, Sensitivity; SPEC, Specificity; TB, Tuberculosis; Tuberculosis; WHO, World Health Organization

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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Screening_studies Idioma: En Revista: Inf Sci (N Y) Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Bangladesh

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