Cystic Fibrosis (CF) and Primary Ciliary Dyskinesia (PCD) are both inherited respiratory disorders that result in impaired mucociliary clearance, and chronic sinopulmonary disease. Although the current approach to PCD management is extrapolated from ...
Cells must adopt flexible regulatory strategies to make decisions regarding their fate, including differentiation, apoptosis, or survival in the face of various external stimuli. One key cellular strategy that enables these functions is stochastic ge...
Genomic best linear unbiased prediction (GBLUP) is widely used for genomic selection in livestock and crop breeding. There is growing interest in connecting machine learning with genomic breeding value prediction. Although the BLUP formula is itself ...
Artificial neural networks (ANNs) are an important tool for studying neural computation, but many features of the brain are not captured by standard ANN architectures. One notable missing feature in most ANN models is top-down feedback, i.e. projecti...
Effective lung cancer detection from CT scans remains critically challenged by class imbalance where benign and normal cases are underrepresented, leading to biased machine learning models with reduced sensitivity for minority classes and potentially...
Relapse risk in endometrial carcinoma (EC) is strongly influenced by molecular subtype, yet current WHO/ESGO classifications rely on postoperative data, limiting their utility for preoperative decision-making. We developed and compared interpretable ...
Accurate prediction of the set of sequences compatible with a protein-protein interface is an unsolved problem in biology. While supervised sequence-based models trained directly on experimental data can predict variant effects, they often fail to ge...
Acute myeloid leukemia (AML) is a hematological cancer characterized by genetic diversity and poor clinical outcomes. Among various genetic mutations in AML, TP53 mutations have relatively low prevalence and present very dismal survival rates. While ...
Unsupervised learning—learning through repeated exposure without instruction or reward—is central to both machine learning and human cognition, including language acquisition and statistical learning. However, its role in visual perceptual learning (...
Sex classification using neuroimaging data has the potential to revolutionize personalized diagnostics by revealing subtle structural brain differences that underlie sex-specific disease risks. Despite the promise of machine learning, traditional met...
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