Latest AI and machine learning research in stem cell research for healthcare professionals.
Reconstructing cellular trajectories from time-resolved single-cell transcriptomics is fundamental to understanding processes from embryonic development to cancer progression. While single-cell foundation models (scFMs) promise universal biological representations through large-scale pretraining, their capacity to capture the non-linear dynamics governing cell-fate decisions remains uncharacterize...
Identifying predictive biomarkers of immunotherapeutic response in melanoma remains an outstanding challenge. Existing transcriptomic and proteomic profiling methods of the tumor-immune microenvironment are costly and may not faithfully capture modifications actively impacting tumor behavior. Here, we present a non-destructive, single-cell approach combining Raman spectroscopy and machine learning...
Quantitative changes in zebrafish embryonic developmental tempo are key phenotypes in drug screening, genetic perturbation, and environmental stress s...
Background: Current diagnostic criteria for multiple sclerosis (MS) rely on white matter lesions (WMLs), which are not specific and often occur in oth...
Resistance to systemic therapy is a major unmet challenge in pancreatic cancer. To identify potential mechanisms of resistance, we developed a novel 3...
Background Candidemia is a rare but life-threatening bloodstream infection that remains difficult to predict using conventional risk stratification ap...
Human iPSC-derived neuronal networks are increasingly being employed in basic and applied research to enhance translation. Astrocytes are essential fo...
Introduction: Atrial fibrillation (AF), a common arrhythmia, is associated with impaired quality of life (QoL) and increased stroke risk and mortality...
Summary Background Once the treatment starts, early prediction of treatment benefit and its correlation with overall survival (OS) remains challenging...
Hydrogels that mimic the extracellular matrix can create a microenvironment with various physicochemical cues, which significantly influence stem cell...
To empower the iterative assessments involved during a person's rehabilitation, automated assessment of a person's abilities during daily activities r...
Small and Medium Enterprises (SMEs) constitute 99.9% of U.S. businesses and generate 44% of economic activity, yet systematically identifying high-pot...
Machine learning (ML) models are effective at classifying images across various fields, including biology. However, their performance on biomedical im...
We examine whether research systems reallocate scientific effort as health needs change. We assemble a global disease-location panel for 204 countries...
Background: The ability of large language models (LLMs) to work collaboratively and screen studies in a systematic review (SR) is under-explored. Henc...
Compared to immortalized cell lines, patient-derived organoids and other ex vivo models have been shown to better recapitulate patient responses to th...
Over the last 35 years, the sharing of medical data and models for research has evolved from sneakernet to the internet - from mailing magnetic tapes ...
Aging of hematopoietic stem and progenitor cells (HSPCs) impairs regenerative capacity and predisposes to hematological diseases. Here, we constructed...
Ductular Reactions (DRs) are dynamic and complex multicellular responses that occur as a result of various hepatic injuries. Precise identification an...
Background The burden of new HIV infections and HIV-related deaths have declined dramatically in sub-Saharan Africa (SSA). However, current HIV survei...