Yeow LY
Neuroanatomical subtypes of schizophrenia and relationship with illness duration and deficit status
Schizophrenia (SCZ) is a chronic and serious mental illness affecting >27 million worldwide (GBD 2017 Disease and Injury Incidence and Prevalence Collaborators, 2018). Heterogeneity in neurobiology (Voineskos et al., 2020), polygenic scores (Alnæs et al., 2019), symptom presentations (Van Rheenen et al., 2017), treatment responses (Malhotra, 2015), and outcomes (Huber, 1997) and their inter-relationships remain incompletely understood and can potentially confound evaluation and affect management of the condition (Lakhan and Vieira, 2009). Grouping patients by clinical subtypes allows for a deeper examination of homogenous groups, and this is often done using measures which assess symptomatology (e.g positive/negative symptom domains), cognitive status or illness course (e.g remission status) (Tan et al., 2020; Weinberg et al., 2016; Wong et al., 2020). Previous studies have attempted to link these clinical subtypes in SCZ based on deficit syndrome (Tan et al., 2020), cognitive functioning (Ho et al., 2020; Seaton et al., 2001; Weinberg et al., 2016) and remission status (Wong et al., 2020) with underlying neural substrates.
ReadCAFT: a deep learning‑based comprehensive abdominal fat analysis tool for large cohort studies
Background There is increasing appreciation of the association of obesity beyond co-morbidities, such as cancers, Type 2 diabetes, hypertension, and stroke to also impact upon the muscle to give rise to sarcopenic obesity. Phenotypic knowledge of obesity is crucial for profiling and management of obesity, as different fat—subcutaneous adipose tissue depots (SAT) and visceral adipose tissue depots (VAT) have various degrees of influence on metabolic syndrome and morbidities. Manual segmentation is time consuming and laborious. Study focuses on the development of a deep learning-based, complete data processing pipeline for MRI-based fat analysis, for large cohort studies which include (1) data augmentation and preprocessing (2) model zoo (3) visualization dashboard, and (4) correction tool, for automated quantification of fat compartments SAT and VAT.
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