Now showing items 1-5 of 5

    • A sentiment classification model based on multiple classifiers 

      Çatal, Çağatay; Nanğır, Mehmet (Elsevier Science Bv, Po Box 211, 1000 AE Amsterdam, Netherlands, 2017-01)
      With the widespread usage of social networks, forums and blogs, customer reviews emerged as a critical factor for the customers' purchase decisions. Since the beginning of 2000s, researchers started to focus on these reviews ...
    • A smart wearable system for short-term cardiovascular risk assessment with emotional dynamics 

      Patlar Akbulut, Fatma; Akan, Aydın (Elsevier Sci Ltd, The Boulevard, Langford Lane, Kidlington, Oxford Ox5 1Gb, Oxon, England, 2018-11)
      Recent innovative treatment and diagnostic methods developed for heart and circulatory system disorders do not provide the desired results as they are not supported by long-term patient follow-up. Continuous medical support ...
    • Automatic energy expenditure measurement for health science 

      Çatal, Çağatay; Akbulut, Akhan (Elsevier Ireland Ltd, Elsevier House, Brookvale Plaza, East Park Shannon, Co, Clare, 00000, Ireland, 2018-04)
      Background and objective: It is crucial to predict the human energy expenditure in any sports activity and health science application accurately to investigate the impact of the activity. However, measurement of the real ...
    • Fetal health status prediction based on maternal clinical history using machine learning techniques 

      Akbulut, Akhan; Ertuğrul, Egemen (Elsevier Ireland Ltd, Elsevier House, Brookvale Plaza, East Park Shannon, Co, Clare, 00000, Ireland, 2018)
      Background and Objective: Congenital anomalies are seen at 1-3% of the population, probabilities of which are tried to be found out primarily through double, triple and quad tests during pregnancy. Also, ultra-sonographical ...
    • On the use of ensemble of classifiers for accelerometer-based activity recognition 

      Çatal, Çağatay; Tüfekçi, Selin; Pirmit, Elif; Kocabağ, Güner (ELSEVIER SCIENCE BV, PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS, 2015-12)
      Activity recognition aims to detect the physical activities such as walking, sitting, and jogging performed by humans. With the widespread adoption and usage of mobile devices in daily life, several advanced applications ...