Mutation

Predicting Diabetic Retinopathy Using a Machine Learning Approach Informed by Whole-Exome Sequencing Studies.

Biomedical and environmental sciences : BES Jan 20, 2025

OBJECTIVE: To establish and validate a novel diabetic retinopathy (DR) risk-prediction model using a whole-exome sequencing (WES)-based machine learning (ML) method.

Pedigree Exome Sequencing Genetic Predisposition to Disease Polymorphism, Single Nucleotide Mutation Diabetic Retinopathy Machine Learning Female Aged Adult Male Middle Aged Diabetes Mellitus, Type 2 Humans

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SCREEN: A Graph-based Contrastive Learning Tool to Infer Catalytic Residues and Assess Enzyme Mutations.

Genomics, proteomics & bioinformatics Jan 15, 2025

The accurate identification of catalytic residues contributes to our understanding of enzyme functions in biological processes and pathways. The increasing number of protein sequences necessitates computational tools for the automated prediction of c...

Computational Biology Humans Mutation Neural Networks, Computer Catalytic Domain Machine Learning Enzymes Software

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Deep Learning-Based SD-OCT Layer Segmentation Quantifies Outer Retina Changes in Patients With Biallelic RPE65 Mutations Undergoing Gene Therapy.

Investigative ophthalmology & visual science Jan 2, 2025

PURPOSE: To quantify outer retina structural changes and define novel biomarkers of inherited retinal degeneration associated with biallelic mutations in RPE65 (RPE65-IRD) in patients before and after subretinal gene augmentation therapy with voretig...

Retina Genetic Therapy Retinal Degeneration cis-trans-Isomerases Female Child Young Adult Visual Acuity Adult Humans Tomography, Optical Coherence Male Mutation Middle Aged Deep Learning Adolescent Child, Preschool

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From Pixels to Prognosis: Artificial Intelligence and Machine Learning Models in Brain Tumour Mutation Prediction.

JPMA. The Journal of the Pakistan Medical Association Jan 1, 2025

Brain tumours are a leading cause of death and disability, impacting individuals across all ages, genders, and ethnicities. They are primarily diagnosed using MRI but a precise diagnosis is dependent on the molecular biology of the tumour studied on ...

Humans Artificial Intelligence Mutation Machine Learning Prognosis Brain Neoplasms Magnetic Resonance Imaging

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Enhancing Molecular Network-Based Cancer Driver Gene Prediction Using Machine Learning Approaches: Current Challenges and Opportunities.

Journal of cellular and molecular medicine Jan 1, 2025

Cancer is a complex disease driven by mutations in the genes that play critical roles in cellular processes. The identification of cancer driver genes is crucial for understanding tumorigenesis, developing targeted therapies and identifying rational ...

Humans Neural Networks, Computer Machine Learning Computational Biology Neoplasms Mutation Protein Interaction Maps Oncogenes Gene Regulatory Networks

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Explainable Machine Learning Predictions for the Benefit From Chemotherapy in Advanced Non-Small Cell Lung Cancer Without Available Targeted Mutations.

The clinical respiratory journal Dec 1, 2024

BACKGROUND: Non-small cell lung cancer (NSCLC) is a global health challenge. Chemotherapy remains the standard therapy for advanced NSCLC without mutations, but drug resistance often reduces effectiveness. Developing more effective methods to predict...

Prognosis Retrospective Studies Female Aged Adult Male Middle Aged China Humans Machine Learning Mutation Lymphocytes Lung Neoplasms Antineoplastic Combined Chemotherapy Protocols Neutrophils Carcinoma, Non-Small-Cell Lung

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Building a Risk Scoring Model for ARDS in Lung Adenocarcinoma Patients Using Machine Learning Algorithms.

Journal of cellular and molecular medicine Dec 1, 2024

Lung adenocarcinoma (LUAD), the predominant form of non-small-cell lung cancer, is frequently complicated by acute respiratory distress syndrome (ARDS), which increases mortality risks. Investigating the prognostic implications of ARDS-related genes ...

DNA Copy Number Variations Mutation Adenocarcinoma of Lung Lung Neoplasms Gene Expression Regulation, Neoplastic Respiratory Distress Syndrome Algorithms Prognosis Female Risk Factors Biomarkers, Tumor Male Risk Assessment Gene Expression Profiling Humans Machine Learning

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Raman-based machine-learning platform reveals unique metabolic differences between IDHmut and IDHwt glioma.

Neuro-oncology Nov 4, 2024

BACKGROUND: Formalin-fixed, paraffin-embedded (FFPE) tissue slides are routinely used in cancer diagnosis, clinical decision-making, and stored in biobanks, but their utilization in Raman spectroscopy-based studies has been limited due to the backgro...

Mutation Isocitrate Dehydrogenase Humans Spectrum Analysis, Raman Machine Learning Glioma Biomarkers, Tumor DNA Methylation Brain Neoplasms

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Deep learning-based analysis of EGFR mutation prevalence in lung adenocarcinoma H&E whole slide images.

The journal of pathology. Clinical research Nov 1, 2024

EGFR mutations are a major prognostic factor in lung adenocarcinoma. However, current detection methods require sufficient samples and are costly. Deep learning is promising for mutation prediction in histopathological image analysis but has limitati...

Humans ErbB Receptors Lung Neoplasms Female Adenocarcinoma of Lung Mutation Deep Learning Image Interpretation, Computer-Assisted DNA Mutational Analysis

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Diffusion-weighted MRI precisely predicts telomerase reverse transcriptase promoter mutation status in World Health Organization grade IV gliomas using a residual convolutional neural network.

The British journal of radiology Nov 1, 2024

OBJECTIVES: Telomerase reverse transcriptase promoter (pTERT) mutation status plays a key role in making decisions and predicting prognoses for patients with World Health Organization (WHO) grade IV glioma. This study was conducted to assess the valu...

Glioma Predictive Value of Tests Neoplasm Grading Mutation Brain Neoplasms Male Middle Aged Humans Neural Networks, Computer World Health Organization Retrospective Studies Female Promoter Regions, Genetic Aged Diffusion Magnetic Resonance Imaging Adult Telomerase

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AI Medical Compendium Topic

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

Predicting Diabetic Retinopathy Using a Machine Learning Approach Informed by Whole-Exome Sequencing Studies.

SCREEN: A Graph-based Contrastive Learning Tool to Infer Catalytic Residues and Assess Enzyme Mutations.

Deep Learning-Based SD-OCT Layer Segmentation Quantifies Outer Retina Changes in Patients With Biallelic RPE65 Mutations Undergoing Gene Therapy.

From Pixels to Prognosis: Artificial Intelligence and Machine Learning Models in Brain Tumour Mutation Prediction.

Enhancing Molecular Network-Based Cancer Driver Gene Prediction Using Machine Learning Approaches: Current Challenges and Opportunities.

Explainable Machine Learning Predictions for the Benefit From Chemotherapy in Advanced Non-Small Cell Lung Cancer Without Available Targeted Mutations.

Building a Risk Scoring Model for ARDS in Lung Adenocarcinoma Patients Using Machine Learning Algorithms.

Raman-based machine-learning platform reveals unique metabolic differences between IDHmut and IDHwt glioma.

Deep learning-based analysis of EGFR mutation prevalence in lung adenocarcinoma H&E whole slide images.

Diffusion-weighted MRI precisely predicts telomerase reverse transcriptase promoter mutation status in World Health Organization grade IV gliomas using a residual convolutional neural network.

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