Published on in Vol 4, No 4 (2016): Oct-Dec

Increasing Complexity in Rule-Based Clinical Decision Support: The Symptom Assessment and Management Intervention

Increasing Complexity in Rule-Based Clinical Decision Support: The Symptom Assessment and Management Intervention

Increasing Complexity in Rule-Based Clinical Decision Support: The Symptom Assessment and Management Intervention

Journals

  1. Baker E, Walter N, Salo A, Rivas Perea P, Moore S, Gonzales S, Grant K. Identifying Future Drinkers: Behavioral Analysis of Monkeys Initiating Drinking to Intoxication is Predictive of Future Drinking Classification. Alcoholism: Clinical and Experimental Research 2017;41(3):626 View
  2. Basit M, Baldwin K, Kannan V, Flahaven E, Parks C, Ott J, Willett D. Agile Acceptance Test–Driven Development of Clinical Decision Support Advisories: Feasibility of Using Open Source Software. JMIR Medical Informatics 2018;6(2):e23 View
  3. Cooley M, Abrahm J, Berry D, Rabin M, Braun I, Paladino J, Nayak M, Lobach D. Algorithm-based decision support for symptom self-management among adults with Cancer: results of usability testing. BMC Medical Informatics and Decision Making 2018;18(1) View
  4. Chen L, Gu Y, Ji X, Lou C, Sun Z, Li H, Gao Y, Huang Y. Clinical trial cohort selection based on multi-level rule-based natural language processing system. Journal of the American Medical Informatics Association 2019;26(11):1218 View
  5. Chen C, Warikoo N, Chang Y, Chen J, Hsu W. Medical knowledge infused convolutional neural networks for cohort selection in clinical trials. Journal of the American Medical Informatics Association 2019;26(11):1227 View
  6. Eldridge R, Pugh S, Trotti A, Hu K, Spencer S, Yom S, Rosenthal D, Read N, Desai A, Gore E, Shenouda G, Mishra M, Bruner D, Xiao C. Changing functional status within 6 months posttreatment is prognostic of overall survival in patients with head and neck cancer: NRG Oncology Study. Head & Neck 2019;41(11):3924 View
  7. Chen S, Wu S. Identifying Lung Cancer Risk Factors in the Elderly Using Deep Neural Networks: Quantitative Analysis of Web-Based Survey Data. Journal of Medical Internet Research 2020;22(3):e17695 View
  8. Back A, Friedman T, Abrahm J. Palliative Care Skills and New Resources for Oncology Practices: Meeting the Palliative Care Needs of Patients With Cancer and Their Families. American Society of Clinical Oncology Educational Book 2020;(40):14 View
  9. Flannery M, Stein K, Dougherty D, Mohile S, Guido J, Wells N. Nurse-Delivered Symptom Assessment for Individuals With Advanced Lung Cancer. Oncology Nursing Forum 2018;45(5):619 View
  10. Yaya S, Idriss-Wheeler D, Sanogo N, Vezina M, Bishwajit G. Self-reported activities of daily living, health and quality of life among older adults in South Africa and Uganda: a cross sectional study. BMC Geriatrics 2020;20(1) View
  11. Cooley M, Mazzola E, Xiong N, Hong F, Lobach D, Braun I, Halpenny B, Rabin M, Johns E, Finn K, Berry D, McCorkle R, Abrahm J. Clinical Decision Support for Symptom Management in Lung Cancer Patients: A Group RCT. Journal of Pain and Symptom Management 2022;63(4):572 View
  12. Papadopoulos P, Soflano M, Chaudy Y, Adejo W, Connolly T. A systematic review of technologies and standards used in the development of rule-based clinical decision support systems. Health and Technology 2022;12(4):713 View
  13. Jones E, Hultman G, Schmoke K, Ninkovic I, Dodge S, Bahr M, Melton G, Marquard J, Tignanelli C. Combined Expert and User-Driven Usability Assessment of Trauma Decision Support Systems Improves User-Centered Design. Surgery 2022;172(5):1537 View
  14. Wang Y, Allsop M, Epstein J, Howell D, Rapoport B, Schofield P, Van Sebille Y, Thong M, Walraven I, Ryan Wolf J, van den Hurk C. Patient-reported symptom monitoring: using (big) data to improve supportive care at the macro-, meso-, and micro-levels. Supportive Care in Cancer 2024;32(3) View
  15. Yackel H, Halpenny B, Abrahm J, Ligibel J, Enzinger A, Lobach D, Cooley M. A qualitative analysis of algorithm-based decision support usability testing for symptom management across the trajectory of cancer care: one size does not fit all. BMC Medical Informatics and Decision Making 2024;24(1) View
  16. Xiao J, Peng Y, Li Y, Ye F, Zeng Z, Lin X, Xie Y, Cheng S, Wen Y, Luo W. Exploring the symptoms and psychological experiences among lung cancer convalescence patients after radical lobectomy: A qualitative study. Cancer Medicine 2024;13(15) View

Books/Policy Documents

  1. Panda S, Biswal S, Rath S, Saxena S. Radiomics and Radiogenomics in Neuro-Oncology. View