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Construction and application of medication reminder system: intelligent generation of universal medication schedule
BackgroundPatients with chronic conditions need multiple medications daily to manage their condition. However, most patients have poor compliance,...
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Building RadiologyNET: an unsupervised approach to annotating a large-scale multimodal medical database
BackgroundThe use of machine learning in medical diagnosis and treatment has grown significantly in recent years with the development of...
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Transcriptome- and DNA methylation-based cell-type deconvolutions produce similar estimates of differential gene expression and differential methylation
BackgroundChanging cell-type proportions can confound studies of differential gene expression or DNA methylation (DNAm) from peripheral blood...
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Identification of immune-associated biomarkers of diabetes nephropathy tubulointerstitial injury based on machine learning: a bioinformatics multi-chip integrated analysis
BackgroundDiabetic nephropathy (DN) is a major microvascular complication of diabetes and has become the leading cause of end-stage renal disease...
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Electronic medical records imputation by temporal Generative Adversarial Network
The loss of electronic medical records has seriously affected the practical application of biomedical data. Therefore, it is a meaningful research...
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Saliency-driven explainable deep learning in medical imaging: bridging visual explainability and statistical quantitative analysis
Deep learning shows great promise for medical image analysis but often lacks explainability, hindering its adoption in healthcare. Attribution...
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Using GPT-4 to write a scientific review article: a pilot evaluation study
GPT-4, as the most advanced version of OpenAI’s large language models, has attracted widespread attention, rapidly becoming an indispensable AI tool...
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Minimization of occurrence of retained surgical items using machine learning and deep learning techniques: a review
Retained surgical items (RSIs) pose significant risks to patients and healthcare professionals, prompting extensive efforts to reduce their...
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Unveiling wearables: exploring the global landscape of biometric applications and vital signs and behavioral impact
The development of neuroscientific techniques enabling the recording of brain and peripheral nervous system activity has fueled research in cognitive...
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A machine learning approach using conditional normalizing flow to address extreme class imbalance problems in personal health records
BackgroundSupervised machine learning models have been widely used to predict and get insight into diseases by classifying patients based on personal...
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The biomedical knowledge graph of symptom phenotype in coronary artery plaque: machine learning-based analysis of real-world clinical data
A knowledge graph can effectively showcase the essential characteristics of data and is increasingly emerging as a significant means of integrating...
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Machine-learning-based models to predict cardiovascular risk using oculomics and clinic variables in KNHANES
BackgroundRecent researches have found a strong correlation between the triglyceride-glucose (TyG) index or the atherogenic index of plasma (AIP) and...
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Decoding dynamic miRNA:ceRNA interactions unveils therapeutic insights and targets across predominant cancer landscapes
Competing endogenous RNAs play key roles in cellular molecular mechanisms through cross-talk in post-transcriptional interactions. Studies on ceRNA...
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Evaluation of network-guided random forest for disease gene discovery
BackgroundGene network information is believed to be beneficial for disease module and pathway identification, but has not been explicitly utilized...
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MOCAT: multi-omics integration with auxiliary classifiers enhanced autoencoder
BackgroundIntegrating multi-omics data is emerging as a critical approach in enhancing our understanding of complex diseases. Innovative...
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Interpreting drug synergy in breast cancer with deep learning using target-protein inhibition profiles
BackgroundBreast cancer is the most common malignancy among women worldwide. Despite advances in treating breast cancer over the past decades, drug...
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Interaction models matter: an efficient, flexible computational framework for model-specific investigation of epistasis
PurposeEpistasis, the interaction between two or more genes, is integral to the study of genetics and is present throughout nature. Yet, it is seldom...
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Assessment of the causal relationship between gut microbiota and cardiovascular diseases: a bidirectional Mendelian randomization analysis
BackgroundPrevious studies have shown an association between gut microbiota and cardiovascular diseases (CVDs). However, the underlying causal...
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A network-based drug prioritization and combination analysis for the MEK5/ERK5 pathway in breast cancer
BackgroundPrioritizing candidate drugs based on genome-wide expression data is an emerging approach in systems pharmacology due to its holistic...
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m1A-Ensem: accurate identification of 1-methyladenosine sites through ensemble models
Background1-methyladenosine (m1A) is a variant of methyladenosine that holds a methyl substituent in the 1st position having a prominent role in RNA...
