Publications by authors named "B K Ho"
PM pollution is a major global concern, especially in Vietnam, due to its harmful effects on health and the environment. Monitoring local PM levels is crucial for assessing air quality. However, Vietnam's state-of-the-art (SOTA) dataset with a 3 km resolution needs to be revised to depict spatial variation in smaller regions accurately.
View Article and Find Full Text PDFBackground: Interpreting the pathogenicity of genetic variants associated with rare diseases is a laborious and time-consuming endeavour. To streamline the diagnostic process and lighten the burden of variant interpretation, it is crucial to automate variant annotation and prioritization. Unfortunately, currently available variant interpretation tools lack a unified and comprehensive workflow that can collectively assess the clinical significance of these types of variants together: small nucleotide variants (SNVs), small insertions/deletions (INDELs), copy number variants (CNVs) and structural variants (SVs).
View Article and Find Full Text PDFExisting microbiota databases are biased toward adult samples, hampering accurate profiling of the infant gut microbiome. Here, we generated a metagenome-assembled genome inventory for children (MAGIC) from a large collection of bulk and viral-like particle-enriched metagenomes from 0 to 7 years of age, encompassing 3,299 prokaryotic and 139,624 viral species-level genomes, 8.5% and 63.
View Article and Find Full Text PDFArticle Synopsis
- Neoadjuvant chemotherapy (NAC) is being increasingly utilized for breast cancer treatment, and machine learning (ML) models are being tested to predict the likelihood of a pathologic complete response (pCR) based on clinical features of patients.
- In a study involving 499 breast cancer patients from two Singapore hospitals, various ML models were trained and evaluated, utilizing methods for addressing missing data, with the random forest model showing the highest predictive accuracy and calibration.
- Key predictors for achieving pCR included estrogen receptor intensity, HER2 intensity, and age at diagnosis, while better handling of missing data led to improved predictive performance in terms of positive and negative predictive values.
Purpose: To characterize the population of surgeons performing anterior cruciate ligament reconstructions (ACLRs) in the United States and investigate the relationships between surgeon volume, career duration, and practice setting on surgical outcomes.
Methods: A large nationwide insurance database was queried for patients undergoing primary ACLR. Provider gender, degree type (allopathic vs osteopathic), practice setting (academic vs private as defined by ACGME affiliation), surgeon volume per year, and career duration were obtained.