A Comparative Analysis of Machine-Learning Algorithms for Automated International Classification of Diseases (ICD)-10 Coding in Malaysian Death Records.

Objective: This study explores machine learning (ML) for automating unstructured textual data translation into structured International Classification of Diseases (ICD)-10 codes, aiming to identify algorithms that enhance mortality data accuracy and reliability for public health decisions.

Methods: This study analyzed death records from January 2017 to June 2022, sourced from Malaysia's Health Informatics Centre, coded into ICD-10. Data anonymization adhered to ethical standards, with 387,650 death registrations included after quality checks.

Identification of novel BCR::ABL1 kinase domain mutation in patients with chronic myeloid leukaemia and imatinib resistance.

Introduction: The emergence of mutations in the BCR::ABL1 kinase domain (KD) impairs imatinib mesylate (IM) binding capacity, thus contributing to IM resistance. Identification of these mutations is important for treatment decisions and precision medicine in chronic myeloid leukaemia (CML) patients. Our study aims to determine the frequency of BCR::ABL1 KD mutations in CML patients with IM resistance.

Mutation analysis of BCR-ABL1 kinase domain in chronic myeloid leukemia patients with tyrosine kinase inhibitors resistance: a Malaysian cohort study.

Objective: Mutational analysis of BCR::ABL1 kinase domain (KD) is a crucial component of clinical decision algorithms for chronic myeloid leukemia (CML) patients with failure or warning responses to tyrosine kinase inhibitor (TKI) therapy. This study aimed to detect BCR::ABL1 KD mutations in CML patients with treatment resistance and assess the concordance between NGS (next generation sequencing) and Sanger sequencing (SS) in detecting these mutations.

Results: In total, 12 different BCR::ABL1 KD mutations were identified by SS in 22.

Corrigendum: Introducing a healthcare-assistive robot in primary care: a preliminary questionnaire survey.

[This corrects the article DOI: 10.3389/frobt.2023.

Introducing a healthcare-assistive robot in primary care: a preliminary questionnaire survey.

A Healthcare-assistive Infection-control RObot (HIRO) is a healthcare-assistive robot that is deployed in an outpatient primary care clinic to sanitise the premises, monitor people in its proximity for their temperature and donning of masks, and usher them to service points. This study aimed to determine the acceptability, perceptions of safety, and concerns among the patients, visitors, and polyclinic healthcare workers (HCWs) regarding the HIRO. A cross-sectional questionnaire survey was conducted from March to April 2022 when the HIRO was at Tampines Polyclinic in eastern Singapore.