6 research outputs found
Data Fusion and Systems Engineering Approaches for Quality and Performance Improvement of Health Care Systems: From Diagnosis to Care to System-level Decision-making
abstract: Technology advancements in diagnostic imaging, smart sensing, and health information systems have resulted in a data-rich environment in health care, which offers a great opportunity for Precision Medicine. The objective of my research is to develop data fusion and system informatics approaches for quality and performance improvement of health care. In my dissertation, I focus on three emerging problems in health care and develop novel statistical models and machine learning algorithms to tackle these problems from diagnosis to care to system-level decision-making.
The first topic is diagnosis/subtyping of migraine to customize effective treatment to different subtypes of patients. Existing clinical definitions of subtypes use somewhat arbitrary boundaries primarily based on patient self-reported symptoms, which are subjective and error-prone. My research develops a novel Multimodality Factor Mixture Model that discovers subtypes of migraine from multimodality imaging MRI data, which provides complementary accurate measurements of the disease. Patients in the different subtypes show significantly different clinical characteristics of the disease. Treatment tailored and optimized for patients of the same subtype paves the road toward Precision Medicine.
The second topic focuses on coordinated patient care. Care coordination between nurses and with other health care team members is important for providing high-quality and efficient care to patients. The recently developed Nurse Care Coordination Instrument (NCCI) is the first of its kind that enables large-scale quantitative data to be collected. My research develops a novel Multi-response Multi-level Model (M3) that enables transfer learning in NCCI data fusion. M3 identifies key factors that contribute to improving care coordination, and facilitates the design and optimization of nurses’ training, workload assignment, and practice environment, which leads to improved patient outcomes.
The last topic is about system-level decision-making for Alzheimer’s disease early detection at the early stage of Mild Cognitive Impairment (MCI), by predicting each MCI patient’s risk of converting to AD using imaging and proteomic biomarkers. My research proposes a systems engineering approach that integrates the multi-perspectives, including prediction accuracy, biomarker cost/availability, patient heterogeneity and diagnostic efficiency, and allows for system-wide optimized decision regarding the biomarker testing process for prediction of MCI conversion.Dissertation/ThesisDoctoral Dissertation Industrial Engineering 201
Case series of breast fillers and how things may go wrong: radiology point of view
INTRODUCTION: Breast augmentation is a procedure opted by women to overcome sagging
breast due to breastfeeding or aging as well as small breast size. Recent years have shown the
emergence of a variety of injectable materials on market as breast fillers. These injectable
breast fillers have swiftly gained popularity among women, considering the minimal
invasiveness of the procedure, nullifying the need for terrifying surgery. Little do they know
that the procedure may pose detrimental complications, while visualization of breast
parenchyma infiltrated by these fillers is also deemed substandard; posing diagnostic
challenges. We present a case series of three patients with prior history of hyaluronic acid and
collagen breast injections.
REPORT: The first patient is a 37-year-old lady who presented to casualty with worsening
shortness of breath, non-productive cough, central chest pain; associated with fever and chills
for 2-weeks duration. The second patient is a 34-year-old lady who complained of cough, fever
and haemoptysis; associated with shortness of breath for 1-week duration. CT in these cases
revealed non thrombotic wedge-shaped peripheral air-space densities.
The third patient is a 37‐year‐old female with right breast pain, swelling and redness for 2-
weeks duration. Previous collagen breast injection performed 1 year ago had impeded
sonographic visualization of the breast parenchyma. MRI breasts showed multiple non-
enhancing round and oval shaped lesions exhibiting fat intensity.
CONCLUSION: Radiologists should be familiar with the potential risks and hazards as well
as limitations of imaging posed by breast fillers such that MRI is required as problem-solving
tool
Characterization of alar ligament on 3.0T MRI: a cross-sectional study in IIUM Medical Centre, Kuantan
INTRODUCTION: The main purpose of the study is to compare the normal anatomy of alar
ligament on MRI between male and female. The specific objectives are to assess the prevalence
of alar ligament visualized on MRI, to describe its characteristics in term of its course, shape and
signal homogeneity and to find differences in alar ligament signal intensity between male and
female. This study also aims to determine the association between the heights of respondents
with alar ligament signal intensity and dimensions.
MATERIALS & METHODS: 50 healthy volunteers were studied on 3.0T MR scanner
Siemens Magnetom Spectra using 2-mm proton density, T2 and fat-suppression sequences. Alar
ligament is depicted in 3 planes and the visualization and variability of the ligament courses,
shapes and signal intensity characteristics were determined. The alar ligament dimensions were
also measured.
RESULTS: Alar ligament was best depicted in coronal plane, followed by sagittal and axial
planes. The orientations were laterally ascending in most of the subjects (60%), predominantly
oval in shaped (54%) and 67% showed inhomogenous signal. No significant difference of alar
ligament signal intensity between male and female respondents. No significant association was
found between the heights of the respondents with alar ligament signal intensity and dimensions.
CONCLUSION: Employing a 3.0T MR scanner, the alar ligament is best portrayed on coronal
plane, followed by sagittal and axial planes. However, tremendous variability of alar ligament as
depicted in our data shows that caution needs to be exercised when evaluating alar ligament,
especially during circumstances of injury