Medicare

Integrating Mutation and Stop Signals for Improved RNA Structure Analysis and Insight Discovery

Understanding RNA structures is essential for exploring its diverse cellular roles. Chemical modification-based RNA structure probing remains a key approach to revealing RNA structures in complex in vivo conditions. Practically, chemical modifications generate both mutation and stop signals during reverse transcription within a single experiment. However, traditional analysis pipelines often rely ...

Multi-modal data integration for machine learning applications

The integration of multi-modal genomic data, encompassing sequences, annotations, and coverage tracks, remains a major bottleneck in bioinformatics, both for exploratory data analysis and machine learning applications. Current approaches rely on several specialized tools for different data modalities, leading to inefficient workflows and computational overhead. Here, we present momics, a unified f...

From Circles to Signals: Representation Learning on Ultra-Long Extrachromosomal Circular DNA

Extrachromosomal circular DNA (eccDNA) is a covalently closed circular DNA molecule that plays an important role in cancer biology. Genomic foundation...

ARCLID: Accurate and Robust Characterization of Long Insertions and Deletions in Genome

Structural variants (SVs) play crucial roles in genome diversity and disease, yet their accurate detection remains challenging, particularly under low...

Clair-Mosaic: A deep-learning method for long-read mosaic small variant calling

Mosaic variants, defined as postzygotic mutations occurring during an organism’s development from zygote to adult, play critical roles in developmenta...

Inhibitory cell type heterogeneity in a spatially structured mean-field model of V1

Inhibitory interneurons in the cortex are classified into cell types differing in their morphology, electrophysiology, and connectivity. Although it i...

Rubisco is slow across the tree of life

Rubisco is the main gateway through which inorganic carbon enters the biosphere, catalyzing the vast majority of carbon fixation on Earth. This pivota...

Deep learning analyses of DNA sequences resolve the retention of the Duffy-null resistance to Plasmodium vivax malaria in Africa

P. vivax, the most geographically widespread human malaria parasite with millions of clinical cases per year, is however quasi absent in sub-Saharan A...

Accurate Variant Classification in Tumour-Only Genomic Data Using Interpretable Tabular Models

Recent work has shown that machine learning can provide a reliable tool to classify somatic and rare germline variants in cancer studies where matched...

A foundational model for joint sequence-function multi-species modeling at scale for long-range genomic prediction

Genomic prediction and design require models that integrate local sequence features with long-range regulatory dependencies spanning hundreds of kilob...

SNooPy: a statistical framework for long-read metagenomic variant calling

Current long-read single-nucleotide variant callers were designed primarily for genomic data—particularly human genomes. While some have been used on ...

MS4MS: LLMs-driven Multi-agent System for Small-molecule Identification via LC-MS/MS

Small molecule identification is central to research fields such as drug discovery, but in complex systems like Traditional Chinese Medicine (TCM), tr...

Care Phenotypes In Critical Care

The Social Determinants of Health (SDoH) have long been recognised as significant drivers of health inequalities. Within healthcare settings, large EH...

Utilization Analysis and Fraud Detection in Medicare via Machine Learning

Healthcare fraud and overutilization pose significant challenges in the United States, leading to substantial financial losses and compromised patient...

Not Such a Long Way Off? Contemporary Artificial intelligence Performance Evaluation on Adult Medicine “Long Cases”

The Royal Australasian College of Physicians (RACP) “Long Cases” assess a trainee’s clinical reasoning beyond what is tested in multiple-choice questi...

Using large language models to understand the public discourse towards vaccination in Brazil between January 2013 and December 2019

Vaccination against infectious diseases prevents diseases, saves lives, and reduces healthcare costs. However, trust, accessibility, and public percep...

A Machine-Learning Approach to Finding Gene Target Treatment Options for Long COVID

Long COVID, also known as post-acute sequelae of SARS-CoV-2 infection (PASC), encompasses a range of symptoms persisting for weeks or months after the...

Natural language processing for scalable feature engineering and ultra-high-dimensional confounding adjustment in healthcare database studies

To improve confounding control in healthcare database studies, data-driven algorithms may empirically identify and adjust for large numbers of pre-exp...

Leveraging artificial Intelligence and online psychotherapy to achieve efficient and coordinated services within a healthcare setting: A quality improvement initiative

This study aimed to implement an artificial intelligence-assisted psychiatric triage program, assessing its impact on efficiency and resource optimiza...

A Deep Learning Framework for Causal Inference in Clinical Trial Design: The CURE AI Large Clinicogenomic Foundation Model

Clinical research is limited by the capability to define the most important combinations of clinical features and biomarkers that predict therapeutic ...