Genetics

Discovering genetic biomarkers for targeted cancer therapeutics with eXplainable Artificial Intelligence.

Real-World Outcomes of Patients with Advanced Epidermal Growth Factor Receptor-Mutated Non-Small Cell Lung Cancer in Canada Using Data Extracted by Large Language Model-Based Artificial Intelligence.

Real-world evidence for patients with advanced -mutated non-small cell lung cancer (NSCLC) in Canada...

Simplified detection of genetic background admixture using artificial intelligence.

Admixture refers to the mixing of genetic ancestry from different populations. Admixture is importan...

Towards classification and comprehensive analysis of AI-based COVID-19 diagnostic techniques: A survey.

The unpredictable pandemic came to light at the end of December 2019, known as the novel coronavirus...

Graph Node Classification to Predict Autism Risk in Genes.

This study explores the genetic risk associations with autism spectrum disorder (ASD) using graph ne...

A radiogenomic multimodal and whole-transcriptome sequencing for preoperative prediction of axillary lymph node metastasis and drug therapeutic response in breast cancer: a retrospective, machine learning and international multicohort study.

BACKGROUND: Axillary lymph nodes (ALN) status serves as a crucial prognostic indicator in breast can...

Electrophysiological and Visual Parameter Changes in Retinitis Pigmentosa Patients undergoing Autologous Platelet-Rich Plasma Therapy: A Randomized Control Trial.

PURPOSE: To assess the efficacy of autologous platelet-rich plasma (PRP) injections in suprachoroida...

Inference of Developmental Hierarchy and Functional States of Exhausted T Cells from Epigenetic Profiles with Deep Learning.

Exhausted T cells are a key component of immune cells that play a crucial role in the immune respons...

Innovations in Medicine: Exploring ChatGPT's Impact on Rare Disorder Management.

Artificial intelligence (AI) is rapidly transforming the field of medicine, announcing a new era of ...

Self-replicating artificial neural networks give rise to universal evolutionary dynamics.

In evolutionary models, mutations are exogenously introduced by the modeler, rather than endogenousl...

RNA3DB: A structurally-dissimilar dataset split for training and benchmarking deep learning models for RNA structure prediction.

With advances in protein structure prediction thanks to deep learning models like AlphaFold, RNA str...

Evaluation of Clinically Significant miRNAs Level by Machine Learning Approaches Utilizing Total Transcriptome Data.

Analysis of the mechanisms underlying the occurrence and progression of cancer represents a key obje...

Deep learning in cancer genomics and histopathology.

Histopathology and genomic profiling are cornerstones of precision oncology and are routinely obtain...

Utilizing genomic signatures to gain insights into the dynamics of SARS-CoV-2 through Machine and Deep Learning techniques.

The global spread of the SARS-CoV-2 pandemic, originating in Wuhan, China, has had profound conseque...

Serum Fusion Transcripts to Assess the Risk of Hepatocellular Carcinoma and the Impact of Cancer Treatment through Machine Learning.

Hepatocellular carcinoma (HCC) is one of the most fatal malignancies. Early diagnosis of HCC is cruc...

Non-invasive prediction for pathologic complete response to neoadjuvant chemoimmunotherapy in lung cancer using CT-based deep learning: a multicenter study.

Neoadjuvant chemoimmunotherapy has revolutionized the therapeutic strategy for non-small cell lung c...

BioDeepfuse: a hybrid deep learning approach with integrated feature extraction techniques for enhanced non-coding RNA classification.

The accurate classification of non-coding RNA (ncRNA) sequences is pivotal for advanced non-coding g...

An AI-based approach driven by genotypes and phenotypes to uplift the diagnostic yield of genetic diseases.

Identifying disease-causing variants in Rare Disease patients' genome is a challenging problem. To a...

Machine Learning Analysis Using RNA Sequencing to Distinguish Neuromyelitis Optica from Multiple Sclerosis and Identify Therapeutic Candidates.

This study aims to identify RNA biomarkers distinguishing neuromyelitis optica (NMO) from relapsing-...

Exploring the NRF2-TP53 Signaling Network Through Machine Learning and Pan-Cancer Analysis: Identifying Potential targets for Cancer Prognosis Related to Oxidative Stress.

Oxidative stress (OXS) is closely related to tumor prognosis and immune response, while TP53 integra...

Decoding the glycoproteome: a new frontier for biomarker discovery in cancer.

Cancer early detection and treatment response prediction continue to pose significant challenges. Ca...