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  • Open Access


    Early Diagnosis of Lung Tumors for Extending Patients’ Life Using Deep Neural Networks

    A. Manju1, R. kaladevi2, Shanmugasundaram Hariharan3, Shih-Yu Chen4,5,*, Vinay Kukreja6, Pradip Kumar Sharma7, Fayez Alqahtani8, Amr Tolba9, Jin Wang10

    CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 993-1007, 2023, DOI:10.32604/cmc.2023.039567

    Abstract The medical community has more concern on lung cancer analysis. Medical experts’ physical segmentation of lung cancers is time-consuming and needs to be automated. The research study’s objective is to diagnose lung tumors at an early stage to extend the life of humans using deep learning techniques. Computer-Aided Diagnostic (CAD) system aids in the diagnosis and shortens the time necessary to detect the tumor detected. The application of Deep Neural Networks (DNN) has also been exhibited as an excellent and effective method in classification and segmentation tasks. This research aims to separate lung cancers from images of Magnetic Resonance Imaging… More >

  • Open Access


    Self-Care Assessment for Daily Living Using Machine Learning Mechanism

    Mouazma Batool1, Yazeed Yasin Ghadi2, Suliman A. Alsuhibany3, Tamara al Shloul4, Ahmad Jalal1, Jeongmin Park5,*

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1747-1764, 2022, DOI:10.32604/cmc.2022.025112

    Abstract Nowadays, activities of daily living (ADL) recognition system has been considered an important field of computer vision. Wearable and optical sensors are widely used to assess the daily living activities in healthy people and people with certain disorders. Although conventional ADL utilizes RGB optical sensors but an RGB-D camera with features of identifying depth (distance information) and visual cues has greatly enhanced the performance of activity recognition. In this paper, an RGB-D-based ADL recognition system has been presented. Initially, human silhouette has been extracted from the noisy background of RGB and depth images to track human movement in a scene.… More >

  • Open Access


    Classification of Parkinson Disease Based on Patient’s Voice Signal Using Machine Learning

    Imran Ahmed1, Sultan Aljahdali2, Muhammad Shakeel Khan1, Sanaa Kaddoura3,*

    Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 705-722, 2022, DOI:10.32604/iasc.2022.022037

    Abstract Parkinson’s disease (PD) is a nervous system disorder first described as a neurological condition in 1817. It is one of the more prevalent diseases in the elderly, and Alzheimer’s is the second most common neurodegenerative illness. It impacts the patient’s movement. Symptoms start gradually with tremors, stiffness in movement, and speech and voice disorders. Researches proved that 89% of patients with Parkinson’s has speech disorder including uncertain articulation, hoarse and breathy voice and monotone pitch. The cause behind this voice change is the reduction of dopamine due to damage of neurons in the substantia nigra responsible for dopamine production. In… More >

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