Now showing items 1-3 of 3

    • Deep convolution neural network model to predict relapse in breast cancer 

      Jha, Alokkumar; Verma, Ghanshyam; Khan, Yasar; Mehmood, Qaiser; Rebholz-Schuhmann, Dietrich; Sahay, Ratnesh (IEEE, 2018-12-17)
      A mishap in anti-cancer drug distribution is critical in breast cancer patients due to poor prediction model to identify the treatment regime in ER+ve and ER-ve (Estrogen Receptor (ER)) patients. The traditional method for ...
    • A deep learning approach to genomics data for population scale clustering and ethnicity prediction 

      Karim, Md. Rezaul; Zappa, Achille; Sahay, Ratnesh; Rebholz-Schuhmann, Dietrich (CEUR-WS.org, 2017-05-28)
      The understanding of variations in genome sequences assists us in identifying people who are predisposed to common diseases, solving rare diseases, and finding corresponding population group of the individuals from a ...
    • Toward distributed, global, deep learning using IoT devices 

      Sudharsan, Bharath; Patel, Pankesh; Breslin, John; Ali, Muhammad Intizar; Mitra, Karan; Dustdar, Schahram; Rana, Omer; Jayaraman, Prem Prakash; Ranjan, Rajiv (Institute of Electrical and Electronics Engineers (IEEE), 2021-07-20)
      Deep learning (DL) using large scale, high-quality IoT datasets can be computationally expensive. Utilizing such datasets to produce a problem-solving model within a reasonable time frame requires a scalable distributed ...