A Patient-Centric Healthcare Model Based on Health Recommender Systems

2018 ◽  
pp. 269-276
Author(s):  
Ritika Bateja ◽  
Sanjay Kumar Dubey ◽  
Ashutosh Bhatt
Keyword(s):  
Recommender Systems ◽  
Model Based ◽  
Healthcare Model ◽  
Patient Centric

scholarly journals Robust Model-Based Reliability Approach to Tackle Shilling Attacks in Collaborative Filtering Recommender Systems

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 41782-41798 ◽  
Author(s):  
Santiago Alonso ◽  
Jesus Bobadilla ◽  
Fernando Ortega ◽  
Ricardo Moya
Keyword(s):  
Collaborative Filtering ◽  
Recommender Systems ◽  
Model Based ◽  
Robust Model

scholarly journals A Survey of Collaborative Filtering Techniques

2009 ◽  
Vol 2009 ◽  
pp. 1-19 ◽  
Author(s):  
Xiaoyuan Su ◽  
Taghi M. Khoshgoftaar
Keyword(s):  
Collaborative Filtering ◽  
Recommender Systems ◽  
Privacy Protection ◽  
State Of The Art ◽  
Predictive Performance ◽  
The State ◽  
Data Sparsity ◽  
Research And Practice ◽  
Model Based ◽  
Comprehensive Survey

As one of the most successful approaches to building recommender systems, collaborative filtering (CF) uses the known preferences of a group of users to make recommendations or predictions of the unknown preferences for other users. In this paper, we first introduce CF tasks and their main challenges, such as data sparsity, scalability, synonymy, gray sheep, shilling attacks, privacy protection, etc., and their possible solutions. We then present three main categories of CF techniques: memory-based, model-based, and hybrid CF algorithms (that combine CF with other recommendation techniques), with examples for representative algorithms of each category, and analysis of their predictive performance and their ability to address the challenges. From basic techniques to the state-of-the-art, we attempt to present a comprehensive survey for CF techniques, which can be served as a roadmap for research and practice in this area.

scholarly journals Ethnography Is the Pathmaker to Better Care: Paving the Way to a Patient-centric Healthcare Model

2016 ◽  
Vol 2016 (1) ◽  
pp. 57-70
Author(s):  
CIARA GREEN ◽  
LAURA POLAZZI ◽  
ERIN O'LOUGHLIN ◽  
VITTORIA TRAVERSO
Keyword(s):  
Healthcare Model ◽  
Patient Centric ◽  
The Way

scholarly journals A Review on Design of Integrated Healthcare Model through Performance Excellence Methodologies

2018 ◽  
Vol 3 (1) ◽  
pp. 1-5
Author(s):  
Srideepti Ramayanam ◽  
G.V.R.K Acharayulu ◽  
V.M. Prasad
Keyword(s):  
Value Chain ◽  
Evidence Based ◽  
Shared Services ◽  
Performance Excellence ◽  
Care Providers ◽  
Treatment Models ◽  
Healthcare Model ◽  
Revenue Cycle ◽  
Operational Processes ◽  
Patient Centric

Cost based care is evolving as a resolution to address increasing Healthcare costs, and to address the problem of clinical inefficiencies. ‘Cost based care’ therefore is designed to be patient centric. While ‘Cost based care’ helps in addressing the challenge of rising costs and making the care more affordable, it  comes with its own set of challenges for providers as they are paid for better patient outcomes in an evidence based way.  In the regimen of ‘Cost based care’ providers are grappling with reduced reimbursements. Providers are also required to track wide variety of measures to make the care more evidence based. Operations transformation for a healthcare systems means that it makes the processes, efficient, flexible and innovative to suit patient centric treatment models. To achieve this transformation by excluding wastes out of system, make the processes much more efficient, implementation of digital systems across the value chain of the hospital have become the area of focus. Shared Services alteration is a subclass of administrational transformation. It is has a lot of potential to smoke out costs, making operational processes much more efficient by rationalizing functions, like Human Resources, Pathology, Radiology, IT and Supply chain services at Hospitals. Administrational transformation aims to flush out costs, bring transformation in revenue cycle, and focus on Patient centric treatment modules. By implementing data visualization dashboards across the services would enable transparency and trust for patients.

Hybrid attacks on model-based social recommender systems

2017 ◽  
Vol 483 ◽  
pp. 171-181 ◽  
Author(s):  
Junliang Yu ◽  
Min Gao ◽  
Wenge Rong ◽  
Wentao Li ◽  
Qingyu Xiong ◽  
...  
Keyword(s):  
Recommender Systems ◽  
Model Based ◽  
Social Recommender Systems
Sign in / Sign up

Export Citation Format

Share Document