| Uk research software survey 2014 S Hettrick, M Antonioletti, L Carr, N Chue Hong, S Crouch, DC De Roure, ... Zenodo, 2014 | 49 | 2014 |
| SDR-Fi: Deep-learning-based indoor positioning via software-defined radio E Schmidt, D Inupakutika, R Mundlamuri, D Akopian IEEE Access 7, 145784-145797, 2019 | 23 | 2019 |
| Cutting edge: anatomy of BioJS, an open source community for the life sciences G Yachdav, T Goldberg, S Wilzbach, D Dao, I Shih, S Choudhary, ... Elife 4, e07009, 2015 | 23 | 2015 |
| Improving adherence to endocrine hormonal therapy among breast cancer patients: Study protocol for a randomized controlled trial P Chalela, E Munoz, D Inupakutika, S Kaghyan, D Akopian, V Kaklamani, ... Contemporary clinical trials communications 12, 109-115, 2018 | 21 | 2018 |
| Software in reproducible research: advice and best practice collected from experiences at the collaborations workshop S Sufi, NC Hong, S Hettrick, M Antonioletti, S Crouch, A Hay, ... Proceedings of the 1st ACM sigplan workshop on reproducible research …, 2014 | 13 | 2014 |
| Facilitating the development of cross-platform mHealth applications for chronic supportive care and a case study D Inupakutika, S Kaghyan, D Akopian, P Chalela, AG Ramirez Journal of biomedical informatics 105, 103420, 2020 | 9 | 2020 |
| Machine Learning Methods for Discriminating Strain and Temperature Effects on FBG-Based Sensors S Sarkar, D Inupakutika, M Banerjee, M Tarhani, M Shadaram IEEE Photonics Technology Letters 33 (16), 876-879, 2021 | 7 | 2021 |
| Technology-based health promotion: Current state and perspectives in emerging gig economy J Morales, D Inupakutika, S Kaghyan, D Akopian, Z Yin, M Evans, ... Biocybernetics and biomedical engineering 39 (3), 825-842, 2019 | 6 | 2019 |
| UK research software survey 2014 S Hettrick, M Antonioletti, L Carr, N Chue Hong, S Crouch, D De Roure, ... University of Edinburgh on behalf of Software Sustainability Institute, 2015 | 5 | 2015 |
| Integration of NLP and Speech-to-text Applications with Chatbots D Inupakutika, M Nadim, GR Gunnam, S Kaghyan, D Akopian, P Chalela, ... Electronic Imaging 2021, 2021 | 2 | 2021 |
| Performance Assessment of mHealth Apps G Rodriguez, D Inupakutika, S Kaghyan, D Akopian, P Lama, P Chalela, ... 2020 IEEE International Conference on Pervasive Computing and Communications …, 2020 | 2 | 2020 |
| Discrimination of Strain and Temperature effects on FBG-based Sensor using Machine Learning S Sarkar, D Inupakutika, M Banerjee, M Tarhani, MK Eghbal, M Shadaram 2020 IEEE Photonics Conference (IPC), 1-2, 2020 | 2 | 2020 |
| An integration of health tracking sensor applications and elearning environments for cloud-based health promotion campaigns D Inupakutika, GV Natarajan, S Kaghyan, D Akopian, M Evans, Y Zenong, ... Electronic Imaging 2018 (6), 114-1-114-8, 2018 | 2 | 2018 |
| Corrigendum to “Improving adherence to endocrine hormonal therapy among breast cancer patients: Study protocol for a randomized controlled trial”[Contemp. Clin. Trials Commun … P Chalela, E Munoz, D Inupakutika, S Kaghyan, D Akopian, V Kaklamani, ... Contemporary Clinical Trials Communications 14, 2019 | 1 | 2019 |
| Designing apps interoperable and functional on multiple mobile platforms using google environment D Inupakutika, C Basutkar, S Kaghyan, D Akopian, P Chalela, ... Electronic Imaging 2018 (6), 115-1-115-11, 2018 | 1 | 2018 |
| On the Performance of Cloud-Based mHealth Applications: A Methodology on Measuring Service Response Time and a Case Study D Inupakutika, G Rodriguez, D Akopian, P Lama, P Chalela, AG Ramirez IEEE Access 10, 53208-53224, 2022 | | 2022 |
| PROMOTING ADHERENCE TO HORMONE THERAPY AMONG BREAST CANCER PATIENTS THROUGH MHEALTH AND PATIENT NAVIGATION P Chalela, V Cortez, A Flores, E Munoz, P Sukumaran, S Sivak, ... ANNALS OF BEHAVIORAL MEDICINE 56 (SUPP 1), S429-S429, 2022 | | 2022 |
| Chatbot integrated with machine learning deployed in the cloud and performance evaluation GG Reddy, I Devasena, M Rahul, K Sahak, A David Electronic Imaging 34, 1-5, 2022 | | 2022 |
| Improving adherence to hormone therapy among breast cancer patients through a mobile app and patient navigation: Preliminary results P Chalela, E Muhoz, V Cortez, A Flores, P Sukumaran, C Despres, ... Cancer Epidemiology Biomarkers and Prevention, 2022 | | 2022 |
| Abstract PO-082: Improving adherence to hormone therapy among breast cancer patients through a mobile app and patient navigation: Preliminary results P Chalela, E Muñoz, V Cortez, A Flores, P Sukumaran, C Despres, ... Cancer Epidemiology, Biomarkers & Prevention 31 (1_Supplement), PO-082-PO-082, 2022 | | 2022 |
David AkopianProfessor, University of Texas at San AntonioVerified email at utsa.edu
