Results 1 to 10 of 13
The application of AI to data from multiple sources, including health records, smart devices and video for monitoring patient health is a growing area with huge opportunity. We bring together experts in the area for a workshop to discuss open problems and potential collaborations. Schedule: Prof Eiman Kanjo Prof Max Little Prof Chris Yau Local...
Speaker: Dr Fiona Kennedy, Leeds Institute of Health Sciences Summary: Increased moderate to vigorous physical activity (MVPA) can improve clinical and psychosocial outcomes for people living with and beyond cancer (LWBC). APPROACH is funded by Yorkshire Cancer Research and the grant covers both a pilot study and a full scale RCT. The pilot RCT assessed the feasibility...
Speaker bio: Dr Kelly Lloyd is a Research Fellow working in the area of behavioural oncology research at the Leeds Institute of Health Sciences. Her PhD focused on decision-making on aspirin for colorectal cancer prevention among people with Lynch syndrome and the general public, and the decision to prescribe or recommend aspirin among healthcare professionals....
Chair – Zoe Hancox Co -chairs – Tamara, Michal, Asra Speaker - Sam Relton Embark on a journey of collaboration and knowledge-sharing through our upcoming series of 5 meetups, designed to empower you in various aspects of health data science. Together, we will explore strategies for identifying knowledge gaps, mastering grant applications, advancing your career...
Background: There is increasing evidence for the beneficial effects of positive health behaviours, such as regular physical activity (PA) and a healthy diet, on cancer outcomes. The World Cancer Research Fund (WCRF) therefore recommends those living with and beyond cancer (LWBC) follow their PA and dietary guidelines for cancer prevention. However, there is a lack...
Abstract: Free text comments (FTC) of patient-reported outcome measures (PROMS) offer invaluable insight into health-related quality of life (HRQoL). However, extracting meaningful information from FTC is challenging due to the time-consuming nature of manual analysis methods (the common analysis method). However, weakly supervised text classification (WSTC) can be a valuable method of analysis to classify...
Delivered chemotherapy dose intensity in adolescent and young adult germ cell tumours in England: assessment of data quality and consistency from clinical trials compared to national cancer registration data. Abstract: Adolescent and Young Adults (AYA) with germ cell tumours (GCT) have poorer survival rates than children and many older adults with the same cancers. There...
Combining Supervised and Unsupervised Machine Learning for Early Diagnosis of Dementia Despite the increasing availability of health data, clinically translatable methods to predict the conversion from Mild Cognitive Impairment (MCI) to dementia are still lacking. MCI represents a precursor to dementia for many individuals; however, some forms of MCI tend to remain stable over time...
Temporal and longitudinal studies collect information repeatedly over time and are aimed to provide insight in joint changes of variables over time. Nowadays, the collected information per time point is often high dimensional, for example images, multiple omics datasets. Dimension reduction methods such as partial least squares for multiple omics or functional principal component analysis...
Speaker – Dr Sam Smith, Associate Professor in Leeds Institute of Health Sciences, University of Leeds REGISTER NOW Abstract This talk will describe a novel approach for developing and evaluating complex interventions to support behaviour change in the field of cancer prevention and control. This approach, guided by the multiphase optimisation strategy (MOST), advocates for the...