Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 50,291 to 50,300 of 224,814 articles

Analysis of Age-Specific Dysregulation of miRNAs in Lung Cancer Via Machine learning: Biomarker Identification and Therapeutic Implications in Patients Aged 60 and Above.

bioRxiv
Lung cancer is the leading cause of cancer-related mortality worldwide, predominantly affects older individuals, with non-small cell lung cancer (NSCLC) comprising 85% of cases. Despite advancements in diagnosis and treatment, prognosis for elderly p... read more 

Enhancing ML-based binder design with high-throughput screening: a comparison of mRNA and yeast display technologies

bioRxiv
Recent advances in machine learning (ML)-based protein design methods have enabled the rapid in silico generation of large libraries of miniprotein binders with minimal manual input. While computational design capacity has scaled rapidly, experimenta... read more 

evoCancerGPT: Generating Zero-Shot Single-Cell and Single-Sample Cancer Progression Through Transfer Learning

bioRxiv
Cancer evolution is driven by complex changes in gene expression as cells transition and change states during tumorigenesis. Single-cell RNA sequencing has provided snapshot insights into how the transcriptomics of tumors evolve, but whether the exis... read more 

Inferring unobserved vector dynamics for dengue forecasting using physics-informed neural networks and mechanistic transmission models

bioRxiv
Accurately characterising mosquito infection dynamics is essential for effective dengue prevention and control, yet these dynamics are rarely observable through routine surveillance. Here, we integrate a reduced SI-SIR transmission model with monthly... read more 

MassID provides near complete annotation of metabolomics data with identification probabilities

bioRxiv
Liquid chromatography coupled to mass spectrometry (LC/MS) is a powerful tool in metabolomics research, generating tens-of-thousands of signals from a single biological sample. However, current software solutions for unbiased assessment of metabolomi... read more 

Noradrenergic neuromodulation produces a NMDAR-dependent network state of respiratory rhythmogenesis in the preBotzinger Complex

bioRxiv
Norepinephrine (NE) is an important mediator of sympathetic activity that influences breathing. At the level of the inspiratory neural network, the preBotzinger complex (preBotC), NE modulation orchestrates changes in neuronal network dynamics that i... read more 

High-Resolution 3D Histology of the Murine Kidney Using Synchrotron X-Ray Micro-CT

bioRxiv
Conventional two-dimensional (2D) histology relies upon destructive sample preparation and stereological estimation, frequently leading to sampling bias and loss of critical spatial context required for understanding renal structure relationships. He... read more 

Cell phenotypes in the biomedical literature: a systematic analysis and text mining corpus

bioRxiv
The variety of cell phenotypes identified by single-cell technologies is rapidly expanding, yet this knowledge is dispersed across the scientific literature and incompletely represented in structured resources. We present the CellLink corpus, a manua... read more 

Cortical maps diverge, representations converge along cortical hierarchy

bioRxiv
Brain maps (e.g. retinotopy, somatotopy) vary across individuals. This is thought to reflect underlying computational differences. However, artificial neural networks (ANNs) show that similar performance and internal representations can coexist with ... read more 

Generating Biologically Relevant Subtypes of Autism Spectrum Disorder with differential responses to Acute Oxytocin Administration in a Randomized Trial using Random Forest Models and K-means Clustering

medRxiv
Autism Spectrum Disorder (ASD) is a heterogenous condition that has no biologically relevant subtypes yet. Here, we utilized a multidimensional approach considering social deficits in ASD alongside negative valence and empathy dysfunction to distingu... read more