G Space

The Good surrounding AI

Documented gains, ranked by source quality, corroboration, and recency. Reader feedback is shown separately and never changes the evidence rank. 345 records · page 3 of 12.

Reader signal

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Evidence-backed gainPeer-reviewedHealth

A CNN with contrastive learning and mixed-attention fusion of multimodal MRI and demographic data achieved test set ACC 0.855 and AUC 0.919 for preoperative identification of pineal region germinoma, outperforming single-modality models.

Source article: A multimodal MRI-based deep learning model for non-invasive diagnosis of pineal region germinoma

Neuroradiology

Reader signal

How should this claim be treated?

Evidence-backed gainPeer-reviewedHealth

Automated fundus-image analysis for diabetic retinopathy enables earlier screening and classification that can prevent vision loss in diabetic patients.

Source article: A comprehensive review on automated diabetic retinopathy detection and classification using fundus image

Graefe's Archive for Clinical and Experimental Ophthalmology

Reader signal

How should this claim be treated?

Evidence-backed gainPeer-reviewedClimate

Integrating an NDVI-based Productivity Index with regional prediction uncertainty to select four field samples reduced mean field-scale SOC prediction error from 0.24% to 0.18% RMSE, achieving accuracy comparable to using all available field observations.

Source article: Productivity-based sampling for field-scale soil organic carbon mapping: from regional models to carbon farming needs

Environmental Monitoring and Assessment

Reader signal

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Evidence-backed gainPeer-reviewedHealth

Unsupervised hierarchical clustering integrated BMI, activity, comorbidities, HAQ and TNF pathway genetics to identify three RA subgroups with differing TNFi response rates, including a better-prognosis cluster with 73.5% response.

Source article: Clustering of rheumatoid arthritis patients: an unsupervised machine learning approach for characterizing the TNFi response

Immunologic Research

Reader signal

How should this claim be treated?

Evidence-backed gainPeer-reviewedHealth

Psychiatric nursing internship students who used the ChatGPT-based virtual patient with a structured prompting framework showed higher MSE competency after the intervention.

Source article: An AI-Supported Virtual Patient Application Using a Structured Prompting Framework to Develop Mental Status Examination Skills in Psychiatric Nursing Internship Students: An Interventional Mixed-Methods Study

Issues in Mental Health Nursing

Reader signal

How should this claim be treated?

Evidence-backed gainPeer-reviewedScience

A hybrid quantum-classical model combining variational quantum circuits with ESM2 achieved statistically significant improvements over classical baselines for multi-class IDR binding partner prediction.

Source article: Quantum-Enhanced Transfer Learning for IDR Binding Partner Prediction

IEEE Transactions on Computational Biology and Bioinformatics

Reader signal

How should this claim be treated?

Evidence-backed gainPeer-reviewedCrime

A bagging ensemble combining random forest and multilayer perceptron improved landscape ecological vulnerability mapping for riverbank erosion, reaching 0.97 AUC and enabling targeted land management for disaster risk reduction.

Source article: Hybrid ensemble machine learning algorithms for landscape ecological vulnerability assessment to riverbank erosion

Environmental Monitoring and Assessment

Reader signal

How should this claim be treated?

Evidence-backed gainPeer-reviewedHealth

A CoxBoost + survivalSVM prognostic model built from resistance-associated cluster genes achieved C-index 0.686 and stratified LUAD patients with HR 2.54-10.51, with low-risk patients showing greater immune infiltration and ARNTL2 knockdown suppressing proliferation and invasion in A549 and H1299 cells.

Source article: Integration of single-cell transcriptomics and genomic mutation analysis identifies an immunotherapy-resistant tumor subcluster and validates ARNTL2 as a malignant driver in lung adenocarcinoma

Translational Oncology

Reader signal

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Evidence-backed gainPeer-reviewedHealth

AI-enabled intervention delivery for adult cancer survivors was associated with reported improvements in clinical and psychosocial outcomes, with model performance generally moderate to high across symptom tasks.

Source article: Application of Artificial Intelligence (AI) in cancer symptom management for adult cancer survivors: a scoping review

International Journal of Medical Informatics

Reader signal

How should this claim be treated?

Evidence-backed gainPeer-reviewedHealth

A hybrid attention-enhanced segmentation plus morphological feature classification framework classified OA progression stages at 18-month and 30-month follow-ups from OAI longitudinal knee MRI, achieving 86.67% accuracy with Random Forest to support timely treatment decisions.

Source article: Automated diagnostic system for classification of progression stages of osteoarthritis using magnetic resonance imaging

Physica Medica

Reader signal

How should this claim be treated?

Evidence-backed gainPeer-reviewedClimate

Ensemble ML with SHAP clustering achieved R2=0.913 on 2020-2023 regulatory data and identified ten recurrent environmental settings driving PM10, enabling interpretable analysis without chemical speciation.

Source article: Beyond concentration-based analysis: explainable AI identifies environmental settings influencing urban PM 10 variability

Science of The Total Environment

Reader signal

How should this claim be treated?

Evidence-backed gainPeer-reviewedClimate

A probabilistic causal machine learning framework trained on long-term monitoring data from a full-scale wastewater plant can predict N2O hot moments and convert interpretable outputs into risk-decision rules for adaptive aeration and load regulation to reduce emissions.

Source article: Identifying causal pathways and risk-decision rules for nitrous oxide emission hot moments in wastewater treatment plants using probabilistic causal machine learning

Bioresource Technology

Reader signal

How should this claim be treated?

Evidence-backed gainPeer-reviewedHealth

A DWT-HVG framework with Soft Voting Ensemble enabled automated classification of resting-state EEG for ASD screening with 93.54% accuracy and 98.17% AUC in stratified 10-fold cross-validation.

Source article: Automated autism spectrum disorder detection using EEG signals and time-frequency visibility graphs

Neuroscience

Reader signal

How should this claim be treated?

Evidence-backed gainPeer-reviewedHealth

A multi-modal deep learning framework using Heckmatt scores from six key muscles improved speed and diagnostic performance for muscle ultrasound, predicting neuromuscular pathology with an area under the precision-recall curve of 0.87 on a test set of 320 patients.

Source article: A Combined Deep Learning Approach to Screen Patients for Neuromuscular Pathology

Ultrasound in Medicine & Biology

Reader signal

How should this claim be treated?

Evidence-backed gainPeer-reviewedHealth

An AI system using modified U-Net segmentation automatically classified inferior alveolar nerve proximity to impacted mandibular third molars on CBCT with 90.1% accuracy and reduced analysis time from ~189 seconds to ~4.8 seconds compared to expert radiologists.

Source article: Validation of artificial intelligence-assisted CBCT analysis for predicting inferior alveolar nerve proximity to impacted mandibular third molars: a diagnostic accuracy study

BMC Oral Health

Reader signal

How should this claim be treated?

Evidence-backed gainPeer-reviewedHealth

Converting numerical clinical data into 24-bit rectangular coded images and training ResNet architectures improved heart failure survival prediction, reaching reported accuracy up to 0.9617.

Source article: A novel approach for predicting heart failure survival using a rectangular coded network

Physical and Engineering Sciences in Medicine

Reader signal

How should this claim be treated?

Evidence-backed gainPeer-reviewedHealth

An AI model trained on surgical video frames achieved automated real-time detection and segmentation of bladder neck, adenoma and peripheral zone during robot-assisted prostate enucleation with high Dice scores and >60 fps inference.

Source article: Real-time artificial intelligence-based anatomy recognition in single-port transvesical enucleation of the prostate

BJU International

Reader signal

How should this claim be treated?

Evidence-backed gainPeer-reviewedHealth

An AI reinforcement learning model trained on Swedish population data produced efficient, low-cost diagnostic sequences for moderate to severe breathlessness with high diagnostic yield, prioritizing BMI, anxiety/depression, physical activity, and spirometry before lung diffusion, CT, and hemoglobin tests.

Source article: Using AI to determine optimal cost-effective diagnostic pathways for chronic breathlessness

npj Primary Care Respiratory Medicine

Reader signal

How should this claim be treated?

Evidence-backed gainPeer-reviewedHealth

Causal AI integrated into healthcare informatics systems improves personalized clinical decision-making by estimating individual treatment effects and simulating intervention outcomes.

Source article: CAUSAL artificial intelligence and data-driven decision intelligence in personalized medicine: a review of healthcare informatics systems

Personalized Medicine

Reader signal

How should this claim be treated?

Evidence-backed gainPeer-reviewedLabor

A gradient boosting machine trained on survey data from 318 ICU nurses predicted high moral distress with high discrimination using six predictors, preserving accuracy after feature reduction.

Source article: Moral distress risk profiling in ICU nurses: A cross-sectional study

Nursing Ethics

Reader signal

How should this claim be treated?

Evidence-backed gainPeer-reviewedHealth

Integration of multi-omics and machine learning can improve cardiovascular disease management by supporting definitive and early diagnosis, severity assessment, full-course risk stratification, and individualized prediction of drug and surgical benefit-risk to inform decisions.

Source article: Machine learning and multi-omics technologies for precision cardiovascular medicine: advancing diagnosis, risk prediction, and therapeutic guidance

Frontiers in Cardiovascular Medicine

Reader signal

How should this claim be treated?

Evidence-backed gainPeer-reviewedHealth

Integrating pathology foundation models and multimodal AI to connect histology, genomics, spatial biology and longitudinal monitoring enables evolution-aware prediction of lymph-node metastasis and recurrence risk in colorectal cancer.

Source article: Beyond Morphology: Reframing Lymph-Node Metastasis Prediction Through Clonal Ecology-Decades-Long Genomic Instability and Polyclonal-to-Monoclonal Transitions as the Missing Dimension in Cancer

Stem Cells and Development

Reader signal

How should this claim be treated?

Evidence-backed gainPeer-reviewedHealth

A random forest model using nine routine blood-based predictors can screen for erectile dysfunction risk with high external validation performance, enabling early non-invasive detection during health check-ups.

Source article: Identification of Erectile Dysfunction From Routine Blood Test Data: Development and Validation of a Machine Learning-Based Prediction Model

Andrology

Reader signal

How should this claim be treated?

Evidence-backed gainPeer-reviewedHealth

A convolutional neural network using standard 12-lead ECGs can estimate elevated NT-proBNP levels with strong correlation and good discrimination in internal and external validation.

Source article: Development and External Validation of an AI-ECG Algorithm for Estimating Elevated Serum NT-proBNP Levels

European Heart Journal - Quality of Care and Clinical Outcomes

Reader signal

How should this claim be treated?

Evidence-backed gainPeer-reviewedScience

A delta-ML graph neural network using GFN2-xTB geometries and DFT single-points as low-fidelity inputs predicted PBE0-D3BJ and PBE-D3BJ level properties of transition metal complexes with higher accuracy and better data efficiency than a conventional benchmark.

Source article: Δ -Machine Learning for the Prediction of Metal Complex Properties

Chemistry – A European Journal

Reader signal

How should this claim be treated?

Evidence-backed gainPeer-reviewedHealth

Applying FDA-cleared SubtleHD enhancement to already diagnostic-quality T1 MRI improved Alzheimer's disease classification performance and allowed models trained on only 70% of enhanced data to match full-data standard-of-care performance.

Source article: Deep Learning-Based Enhancement of Already Diagnostic-Quality MRI for Alzheimer's Disease Classification: Effects on Model Performance and Training Data Requirements

Journal of Magnetic Resonance Imaging

Reader signal

How should this claim be treated?

Evidence-backed gainPeer-reviewedHealth

ML-based phenomapping of 106,490 Danish KC patients identified 7 distinct subgroups differentiated by disease burden, comorbidities and socioeconomic status, providing a basis for tailored clinical pathways.

Source article: Machine-learning-based Phenomapping of Patients with Keratinocyte Carcinoma: Data-driven Subgrouping by Disease Burden, Comorbidities and Socioeconomic Status

Acta Dermato-Venereologica

Reader signal

How should this claim be treated?

Evidence-backed gainPeer-reviewedPolicy

A multi-stage framework integrating YOLOv8 detection, OC-SORT tracking, dynamic CROI filtering, and ST-GAT prediction enables accurate real-time traffic-conflict prediction at signalized intersections to enhance safety and mitigate accident risks.

Source article: Efficient video-based traffic conflict prediction and interpretable risk analysis at signalized intersections via deep learning

Traffic Injury Prevention

Reader signal

How should this claim be treated?

Evidence-backed gainPeer-reviewedHealth

Automated AI segmentation of macular OCT quantified selective inner retinal thinning during silicone oil tamponade and identified RNFL, GCL+IPL and PR+RPE as strongest predictors of visual acuity change, enabling prognostication after oil removal.

Source article: PREDICTIVE OCT BIOMARKERS OF RETINAL CHANGES AND VISUAL OUTCOMES IN SILICONE OIL ENDOTAMPONADE IDENTIFIED BY ARTIFICIAL INTELLIGENCE

Retina

Reader signal

How should this claim be treated?

Evidence-backed gainPeer-reviewedHealth

AI assistance during routine mammography was associated with higher overall cancer detection and no increase in average interpretation time.

Source article: Impact of AI assistance on reading time, cancer detection rate, and abnormal interpretation rate in screening and diagnostic mammography: a prospective alternating-month study

European Radiology