The global annual output of liquid crystal monomers (LCMs) continues to increase, yet associated environmental and health risks remain poorly characterized. Assessing the toxic effects of the LCM mixture and individual components is critical for risk...
BACKGROUND: Lumbar disc degeneration (LDD) displays considerable heterogeneity in terms of clinical features and pathological changes. However, researchers have not clearly determined whether the transcriptome variations in LDD could be used to ident...
BACKGROUND: Coronary artery calcification (CAC) represents a major cardiovascular risk in patients with end-stage renal disease (ESRD) undergoing hemodialysis. Given that radial artery pulse waveforms can reflect vascular status, this study aimed to ...
BACKGROUND: The high rate of repeat attempts among individuals who have previously attempted suicide presents a critical challenge in public health and suicide prevention. While early and targeted intervention is crucial for this high-risk group, eff...
Mass spectrometry‑based proteomics using isobaric labeling technology has become popular for proteomic quantitation. Existing approaches rely on the mechanism of target-decoy search and false discovery rate control to examine whether a peptide-spectr...
Melanoma immunotherapy urgently requires approaches that can accurately predict drug responses to minimize unnecessary treatments. Deep learning models have emerged as powerful tools in this domain due to their robust predictive capabilities. Integra...
Pancreatic cancer is aggressive with high recurrence rates, necessitating accurate prediction models for effective treatment planning, particularly for neoadjuvant chemotherapy or upfront surgery. This study explores the use of variational autoencode...
Understanding diseases as the result of continuous transitions from a healthy system is more realistic than understanding them as discrete states. Here, we designed the spectrum formation approach (SFA), a machine learning-based method that extracts ...
BACKGROUND: Identifying neuroinfectious disease (NID) cases using International Classification of Diseases billing codes is often imprecise, while manual chart reviews are labor-intensive. Machine learning models can leverage unstructured electronic ...
BACKGROUND: HIV remains a global challenge, with stigma, financial constraints, and psychosocial barriers preventing people living with HIV from accessing health care services, driving them to seek information and support on social media. Despite the...
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