Latest AI and machine learning research in hepatitis for healthcare professionals.
The SARS-CoV-2 Delta variant (B.1.617.2), initially classified as a variant of concern due to its enhanced transmissibility and vaccine-escape mutations, underwent further genomic changes following the emergence of the Omicron variant (B.1.1.529). This study investigates the genomic differences in Delta variant spike gene sequences collected before and after the emergence of Omicron. A total of 19...
High genomic variability among viral species makes sequence classification highly dependent on multiple sequence alignment (MSA) methods, which are both computationally intensive and sensitive to data quality issues. To provide a more efficient and robust alternative, we developed DiCNN-UniK, a Dual-Input Convolutional Neural Network (DiCNN) utilizing unique k-mer signatures and universal k-mer li...
Comparative analysis of adaptive immune repertoires at population scale is hampered by two practical bottlenecks: the near-quadratic cost of pairwise ...
Music generation has advanced markedly through multimodal deep learning, enabling models to synthesize audio from text and, more recently, from images...
Background: Liver cancer primarily develops in patients with chronic liver disease (CLD), yet most cases are diagnosed at an advanced stage with poor ...
Safe and effective gene delivery remains a central challenge for therapeutic applications. While non-viral and viral vectors have enabled substantial ...
The ability to interpret, modify, and design DNA has driven many of the most significant advances in modern medicine, from diagnostics, biologics, and...
Background: Post-operative tachycardia is a common and poorly understood complication following the Fontan procedure. Post-operative factors such as s...
The COVID-19 pandemic has profoundly affected global health, driven by the remarkable transmissibility and mutational adaptability of the SARS-CoV-2 v...
Foundation models trained on patient electronic health records (EHRs) hold promise for transforming clinical care by enabling effective decision suppo...
Background: Early and accurate identification of cardiac amyloidosis improves patient outcomes, yet relevant evidence is frequently hidden in free-tex...
Artificial intelligence (AI) models have advanced rapidly, driving breakthroughs in protein structure prediction, functional annotation, and conformat...
Antiphospholipid syndrome (APS) and systemic sclerosis (SSc) are immune-mediated multisystem autoimmune diseases with distinct clinical phenotypes but...
Dengue (DENV), an RNA virus, remains a significant global health threat, particularly in developing regions, with no widely effective antiviral therap...
The accurate identification of antiviral peptides (AVPs) is crucial for novel drug development. However, existing methods still have limitations in ca...
BackgroundSystemic infections are a leading cause of hospitalization and death among patients with cirrhosis. Timely and accurate infection identifica...
Accurately predicting how amino acid substitutions alter protein function is a central challenge in biology, with applications from interpreting disea...
When training machine learning (ML) models for potential deployment in a healthcare setting, it is essential to ensure that they do not replicate or e...
Despite over 13 billion SARS-CoV-2 vaccine doses administered globally, persistent post-vaccination symptoms, termed post-COVID-19 vaccine syndrome (P...
With the rapid advancement of artificial intelligence (AI) and machine learning (ML) technologies, their applications in the medical field have expand...