A novel framework for automated, intelligent extraction and analysis of online support group discussions for cancer related outcomes

No abstract is available for this paper.

• Publication year

  2017

• Venue

  BJU International

• Publication date

  2017-11-01

• Fields of study

  Medicine, Computer Science

• Identifiers
  DOI 10.1111/bju.14036PMID 29058379
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

• Automatic event detection in microblogs using incremental machine learning

  2017cited by this paper
• A Participatory Model for Multi-Document Health Information Summarisation

  2017cited by this paper
• Addressing the Complexities of Big Data Analytics in Healthcare: The Diabetes Screening Case

  2015cited by this paper
• Cancer patients connect on the Internet.

  2012cited by this paper
• Decision‐making in localized prostate cancer: lessons learned from an online support group

  2011cited by this paper
• Breast and Prostate Cancer Online Discussion Boards

  2007cited by this paper

• Artificial Intelligence–Based Co-Facilitator (AICF) for Detecting and Monitoring Group Cohesion Outcomes in Web-Based Cancer Support Groups: Single-Arm Trial Study

  2022cites this paper
• Textual emotion detection in health: Advances and applications

  2022cites this paper
• Natural Language Processing–Based Virtual Cofacilitator for Online Cancer Support Groups: Protocol for an Algorithm Development and Validation Study

  2021influential citation
• Efficacious Study of Specific Co-Creation Policies in the Healthcare Ecosystem

  2020cites this paper
• Can online support groups address psychological morbidity of cancer patients? An artificial intelligence based investigation of prostate cancer trajectories

  2020cites this paper
• Natural Language Processing–Based Virtual Cofacilitator for Online Cancer Support Groups: Protocol for an Algorithm Development and Validation Study (Preprint)

  2020cites this paper
• ASO Author Reflections: Enabling Optimised Delivery of Patient-Centred Cancer Care Using Artificial Intelligence and Data Analytics

  2018cites this paper
• Robotic-assisted vs. open radical prostatectomy: A machine learning framework for intelligent analysis of patient-reported outcomes from online cancer support groups.

  2018cites this paper
• Machine learning to support social media empowered patients in cancer care and cancer treatment decisions

  2018cites this paper
• ASO Author Reflections: Enabling Optimised Delivery of Patient-Centred Cancer Care Using Artificial Intelligence and Data Analytics

  2018cites this paper
• Text Mining for Personalized Knowledge Extraction From Online Support Groups

  2018cites this paper
• The Patient-Reported Information Multidimensional Exploration (PRIME) Framework for Investigating Emotions and Other Factors of Prostate Cancer Patients with Low Intermediate Risk Based on Online Cancer Support Group Discussions

  2018cites this paper
• Urological outcomes in Australia and New Zealand: who's watching?

  2017cites this paper