Latest AI and machine learning research in geriatrics for healthcare professionals.
Inferring chronological age from magnetic resonance imaging (MRI) brain data has become a valuable tool for the early detection of neurodegenerative diseases. We present a method inspired by cosmological techniques for analyzing galaxy surveys, utilizing higher-order summary statistics with multivariate two- and three-point analyses in 3D Fourier space. This method offers physiological interpretab...
Olfactory dysfunction is a frequent yet understudied feature of neurodegenerative spectrum disorders, including Alzheimer’s disease (AD) and Parkinson’s disease (PD). To disentangle the neural substrates of hyposmia across disease spectra, we examined 222 participants from the Parkinson’s and Alzheimer’s disease Dimensional Neuroimaging Initiative cohort. Participants were classified according to ...
Joint pain is an increasing concern for our aging population, as current therapies to slow joint disease progression or reduce pain are largely ineffe...
Systemic chronic inflammation is a major determinant of aging and disease risk, yet current biomarkers such as the Inflammatory Age (iAge) clock and o...
Extrachromosomal circular DNA (eccDNA) is a covalently closed circular DNA molecule that plays an important role in cancer biology. Genomic foundation...
The emergence of large-scale biobanks has opened unprecedented opportunities for the development of data-driven approaches, especially deep learning-b...
The Master Athletic Laboratory Study of Intramuscular Connective Tissue (MALICoT, DRKS00015764) set out to analyze the endomysium content of the human...
Digital language markers show promise in detecting early cognitive impairment related to Alzheimer’s disease (AD), yet their relationship with cerebro...
To construct and validate a deep-learning (DL) model for the automatic quantification of temporalis muscle thickness (TMT) in CT head scans. We develo...
Rare disease variant interpretation requires navigating multiple genomic databases with strict input formats and synthesizing heterogeneous evidence, ...
Spiking Neural Networks (SNNs) have the potential to replicate the brain’s computational efficacy by explicitly incorporating action potentials or “sp...
Therapeutic antibody design is a complex multi-property optimization problem with substantial promise for improvement with the application of machine-...
Drosophila has long served as a powerful model for investigating locomotor behavior, and geotaxis assays have generated valuable insights into genetic...
Yeast replicative lifespan is a crucial part of aging research, yet its quantification remains labor-intensive and time-consuming, particularly when u...
Transcription factors (TFs) are pivotal regulators of gene expression and play essential roles in diverse cellular activities. The three-dimensional o...
MicroRNAs (miRNAs) are small non-coding RNAs that regulate genes by binding to target messenger RNAs (mRNAs), causing them to degrade or suppressing t...
Mosaic variants, defined as postzygotic mutations occurring during an organism’s development from zygote to adult, play critical roles in developmenta...
Alternative splicing (AS) is a fundamental post-transcriptional mechanism that amplifies proteomic diversity and enables adaptive responses across euk...
Understanding how genomic sequences shape three-dimensional (3D) genome architecture is funda-mental to interpreting diverse biological processes. Alt...
Tracking and analyzing animal behaviour is a crucial step in fields such as neuro-science and developmental biology. Behavioral studies in the nematod...