13 papers · ranked by Valyu relevance
Pao‐Yuan Huang, Heng‐Syu Lin, Cheng‐Yuan Peng, Ruei‐Hau Hsu + 1 more
Few prediction models have been specifically designed to evaluate the risk of hepatocellular carcinoma (HCC) in patients with chronic hepatitis B and cirrhosis. This study aimed to develop a machine learning-based prediction model to assess the risk of developing HCC in patients with hepatitis B virus (HBV)-related…
Yasin Topcu, Alper Adak, Halim Can Kayikci, Serkan Aydin + 6 more
Key message Tomato fruit weight is primarily controlled by stable genetic effects and domestication-/improvement-associated loci, including prominent chromosome 5 signals, and integrating SNP, INDEL, and SV diversity improves candidate-locus discovery, biological interpretation, and genomic prediction across…
Shangru Jia, Artem Lysenko, Keith A Boroevich, Alok Sharma + 1 more
Prognostic stratification in multiple myeloma (MM) relies on staging systems fixed at diagnosis, discarding temporal information accumulated during treatment. We developed a dynamic multimodal framework that predicts residual overall survival from observation windows of 1-18 months post-diagnosis. The model integrates…
Sahar Alkhaibari, Feng Dong
Autism spectrum disorder (ASD) is a complex neurodevelopmental condition characterized by persistent difficulties in social communication, social interaction, and repetitive behaviors. Early and accurate diagnosis is essential but is often hindered by subjective clinical assessments, limited data availability, and…
Panagiotis Douris, George Kodovazenitis
The integration of artificial intelligence (AI) into dentistry is reshaping clinical workflows, opening new possibilities for population-level public health monitoring. Machine learning approaches, such as convolutional neural networks and other deep learning architectures, are becoming more and more capable to exhibit…
Nazanin Zahra Keshvari, Sara Asl Motaleb Nejad Sarkhab, Tara Shahmoradi, Mohammad Pourashory + 3 more
Omics datasets are inherently complex and involve an unmanageable number of factors, which render manual/traditional analyses unfruitful. Through the application of data-training protocols, the large number of parameters could be managed. Moreover, ML methods are generally categorized as either: Supervised ML: the…
Lysanne Veerle Michels, Lucy Smith, Suzan Ghannam, Charles Gadd + 1 more
Introduction Artificial intelligence (AI) has rapidly advanced as a key analytical tool for processing complex datasets across disciplines, including environmental and health research. Meteorological data is increasingly used to understand and mitigate health risks, often linked to climate change. This rapid review…
Xiaoyue Hu, Yuhao Ma, Ruixing Ming, Heping Zhang + 1 more
Identifying essential biomarkers remains a core challenge in elucidating the pathogenic mechanisms and achieving precise diagnosis of complex diseases. Deep neural networks offer immense predictive power, yet their lack of interpretability severely limits downstream biological insight. Here, we introduce DeepVaris, an…
Daniel L Riddle, Levent Dumenci
Sir-, Rajamäki and colleagues were interested in identifying preoperative predictors of persistent pain 1-year post-surgery in patients undergoing knee arthroplasty [1]. Given the clinical importance of persistent pain following this typically highly successful surgery, prognostic studies of poor pain outcome are…
Md Shafayet Hossain, Yi-Ping Phoebe Chen
Non-coding RNAs (ncRNAs), once considered genomic dark matter, are now established as key regulators of gene expression with widespread roles in cellular homeostasis and disease. In cancer, ncRNA expression is frequently and systematically dysregulated, and many of these molecules circulate in stable, protected form…
Anni Rajamäki, Aleksi Reito, Mari Karsikas, Mika Niemeläinen + 1 more
Sir,-We thank Dr Riddle and Dr Dumenci for their insightful comments to our article “Predicting persistent pain after total knee arthroplasty using different machine learning algorithms” [1,2]. They highlighted a few important points from the methodology and proposed an alternative statistical approach to predict the…
Hayato Idei, Keisuke Suzuki, Yuichi Yamashita
Mindfulness has established psychological benefits, such as stress reduction and emotional regulation; however, the underlying computational mechanisms, particularly in relation to mind-wandering, remain unclear. This study aimed to present a hierarchical recurrent neural network-based agent model grounded in the free…
Braden Charles DeMattei, Stephanie E. Hampton
Understanding species interactions is integral to understanding ecosystem function and predicting how disturbances may affect the services provided to society. Analysis of trophic interactions, however, requires a significant investment of time and resources. Using a simple predator-prey pairing of a semi-sessile…