Publications by authors named "J Z Lo"
Article Synopsis
- Continuous positive airway pressure (CPAP) is primarily prescribed for obstructive sleep apnea (OSA), but many patients still experience respiratory issues or need higher pressures during treatment.
- The study aimed to create predictive models to better forecast CPAP outcomes using both clinical and physiological data, comparing traditional regression methods to more advanced machine learning techniques.
- Results showed that machine learning models, particularly random forest methods that included physiological traits, significantly outperformed traditional regression models in predicting residual apnea-hypopnea index (AHI), highlighting the importance of using diverse data for more accurate predictions in OSA therapy.
Myeloid cell leukemia 1 (MCL-1) is a member of the B-cell lymphoma 2 protein family and has anti-apoptotic functions. Deregulation of MCL-1 has been reported in several cancers, including lung and breast cancer. In the present study, the association of MCL-1 expression with molecular features in colorectal cancer (CRC) has been highlighted.
View Article and Find Full Text PDFPurpose: We descriptively and comparatively evaluated the comprehensiveness of Canadian and US-accredited ophthalmology residency program websites as of August 28, 2024.
Methods: Using Canadian Resident Matching Service ( = 15) and US Fellowship and Residency Electronic Interactive Database ( = 125), we assessed website content across seven criteria: recruitment, faculty, residents, education/research, teaching, benefits, and community. Two independent reviewers used a 40-point system, with Kruskal-Wallis and post-hoc pairwise tests for analysis by country and funding model.
In this paper, we introduce a novel concordance-based predictive uncertainty (CPU)-Index, which integrates insights from subgroup analysis and personalized AI time-to-event models. Through its application in refining lung cancer screening (LCS) predictions generated by an individualized AI time-to-event model trained with fused data of low dose CT (LDCT) radiomics with patient demographics, we demonstrate its effectiveness, resulting in improved risk assessment compared to the Lung CT Screening Reporting & Data System (Lung-RADS). Subgroup-based Lung-RADS faces challenges in representing individual variations and relies on a limited set of predefined characteristics, resulting in variable predictions.
View Article and Find Full Text PDFBackground: Patients with sepsis-induced AKI can be classified into two distinct sub-phenotypes (AKI-SP1, AKI-SP2) that differ in clinical outcomes and response to treatment. The biologic mechanisms underlying these sub-phenotypes remains unknown. Our objective was to understand the underlying biology that differentiates AKI sub-phenotypes and associations with kidney outcomes.
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