28 August 2024 | 09:55-11:25

Format: Presentation
Stream: Populations

Part 1: Workplace Transformation

Tang Kong Tan Tock Seng Hospital, Singapore

 

Part 2: Impact in terms of quality of a healthcare model for socially vulnerable

The quality of healthcare is generally based on data obtained from population that demands & use health care services. However, less evidence is available from those individuals who are not demanding medical attention and remain at home (which is the 80% of argentininan socially vulnerable population).This proposal shows the impact in terms of quality of care, efficacy and cost-effectiveness of an innovative home care model (nominal & personalized) for socially vulnerable populations at a massive scale when compared results obtained with classical healthcare system based on the spontaneous demand for care provided from health institutions.

Gustavo Marin National University of La Plata, Argentina 

Part 3: Machine learning techniques to predict timeliness of care among lung cancer patients

This research addresses a critical issue in healthcare, specifically focusing on the timely delivery of care for lung cancer patients. Our project leverages state-of-the-art machine-learning techniques to predict the timeliness of care among lung cancer patients using a number of clinical and socio-economic risk factors. We believe that our approach holds significant promise in aiding healthcare providers and administrators in making informed decisions to optimize the delivery of quality of care for lung cancer patients worldwide.

Arul Earnest Monash University, Australia